Query Processing for Distance Metrics. - Jason Tsong-Li Wang; Dennis E. Shasha (VLDB, 1990)

New Techniques for Best-Match Retrieval. - Dennis E. Shasha; Jason Tsong-Li Wang (ACM Trans. Inf. Syst., 1990)

A tool for tree pattern matching. - Jason Tsong-Li Wang; Kaizhong Zhang; Karpjoo Jeong; Dennis E. Shasha (ICTAI, 1991)

Optimizing Equijoin Queries In Distributed Databases Where Relations Are Hash Partitioned. - Dennis E. Shasha; Jason Tsong-Li Wang (ACM Trans. Database Syst., 1991)

Query Optimization in Database and Information Retrieval Systems. - Jason Tsong-Li Wang (1991)

Fast Serial and Parallel Algorithms for Approximate Tree Matching with VLDC's. - Kaizhong Zhang; Dennis E. Shasha; Jason Tsong-Li Wang (CPM, 1992)

Pattern Matching in Unordered Trees. - Dennis E. Shasha; Jason Tsong-Li Wang; Kaizhong Zhang; Frank Yeong-Chyang Shih (ICTAI, 1992)

Texpros: an Intelligent Document Processing System. - Jason T. L. Wang; Peter A. Ng (Int. J. Softw. Eng. Knowl. Eng., 1992)

Nested segmentation: an approach for layout analysis in document classification. - Xiaolong Hao; Jason T. L. Wang; Peter A. Ng (ICDAR, 1993)

A Tool for Classifying Office Documents. - Xiaolong Hao; Jason Tsong-Li Wang; Michael P. Bieber; Peter A. Ng (ICTAI, 1993)

An OI5ce Document Retrieval System with the Capability of Processing Incomplete and Vague Queries. - Qianhong Liu; Jason Tsong-Li Wang; Peter A. Ng (SEKE, 1993)

An Intelligent Documentation Support Environment. - Jason Tsong-Li Wang; Fortune S. Mhlanga; Qianhong Liu; Wen-Chung Shang; Peter A. Ng (SEKE, 1993)

On research issues regarding uncertain query processing in an office document retrieval system. - Qianhong Liu; Jason T. L. Wang; Peter A. Ng (J. Syst. Integr., 1993)

Texpros: an Intelligent Document Processing System. - Jason T. L. Wang; Peter A. Ng (The Impact of Case Technology on Software Processes, 1994)

Document Management Through Hypertext: A Logic Modeling Approach. - Jiangling Wan; Michael P. Bieber; Jason Tsong-Li Wang; Peter A. Ng (HICSS (3), 1994)

The approximate graph matching problem. - Jason T. L. Wang; Kaizhong Zhang; Gung-Wei Chirn (ICPR (2), 1994)

Approximate Graph Matching Using Probabilistic Hill Climbing Algorithms. - Jason Tsong-Li Wang; Kaizhong Zhang; Gung-Wei Chirn (ICTAI, 1994)

A Knowledge-Based Tutoring System for SQL Programming. - Gang Zhou; Jason Tsong-Li Wang; Peter A. Ng (ICTAI, 1994)

DocFlow: an event-driven visual programming environment for office automation through document processing. - Steve C. Y. Chiang; Jason Tsong-Li Wang; Michael P. Bieber; Peter A. Ng (SEKE, 1994)

Combinatorial Pattern Discovery for Scientific Data: Some Preliminary Results. - Jason Tsong-Li Wang; Gung-Wei Chirn; Thomas G. Marr; Bruce A. Shapiro; Dennis E. Shasha; Kaizhong Zhang (SIGMOD Conference, 1994)

Heuristic Classification of Office Documents. - Xiaolong Hao; Jason T. L. Wang; Michael P. Bieber; Peter A. Ng (Int. J. Artif. Intell. Tools, 1994)

Approximate Tree Matching in the Presence of Variable Length Don't Cares. - Kaizhong Zhang; Dennis E. Shasha; Jason Tsong-Li Wang (J. Algorithms, 1994)

A formal approach to modeling office information systems. - Zhijian Zhu; James A. McHugh; Jason T. L. Wang; Peter A. Ng (J. Syst. Integr., 1994)

A System for Approximate Tree Matching. - Jason Tsong-Li Wang; Kaizhong Zhang; Karpjoo Jeong; Dennis E. Shasha (IEEE Trans. Knowl. Data Eng., 1994)

Exact and approximate algorithms for unordered tree matching. - Dennis E. Shasha; Jason Tsong-Li Wang; Kaizhong Zhang; Frank Y. Shih (IEEE Trans. Syst. Man Cybern., 1994)

On the Editing Distance between Undirected Acyclic Graphs and Related Problems. - Kaizhong Zhang; Jason Tsong-Li Wang; Dennis E. Shasha (CPM, 1995)

LHM: a logic-based hypertext data model for integrating hypertext and information systems. - Jiangling Wan; Michael P. Bieber; Jason Tsong-Li Wang; Peter A. Ng (HICSS (3), 1995)

Fast retrieval of electronic documents in digital libraries. - Jason Tsong-Li Wang; Chia-Yo Chang (ICTAI, 1995)

An Integrated Toolkit for Pattern Matching and Pattern Discovery in Scientific, Program, and Document databases. - Jason Tsong-Li Wang; Gung-Wei Chim; Chia-Yo Chang; George Jyh-Shian Chang; Karen Pysniak (SEKE, 1995)

Pattern Matching and Pattern Discovery in Scientific, Program, and Document Databases. - Jason Tsong-Li Wang; Kaizhong Zhang; Dennis E. Shasha (SIGMOD Conference, 1995)

A New Approach to Modeling Personal Office Documents. - Fortune S. Mhlanga; Zhijian Zhu; Jason Tsong-Li Wang; Peter A. Ng (Data Knowl. Eng., 1995)

Algorithms for Approximate Graph Matching. - Jason Tsong-Li Wang; Kaizhong Zhang; Gung-Wei Chirn (Inf. Sci., 1995)

Automated Discovery of Active Motifs in Multiple RNA Secondary Structures. - Jason Tsong-Li Wang; Bruce A. Shapiro; Dennis E. Shasha; Kaizhong Zhang; Chia-Yo Chang (KDD, 1996)

Scientific Data Mining: A Case Study. - Chia-Yo Chang; Jason Tsong-Li Wang (SEKE, 1996)

A Visualization Tool for Pattern Matching and Discovery in Scientific Databases. - George Jyh-Shian Chang; Jason Tsong-Li Wang; Gung-Wei Chirn; Chia-Yo Chang; Weihong Wu; Firas Aljallad (SEKE, 1996)

On the Editing Distance Between Undirected Acyclic Graphs. - Kaizhong Zhang; Jason Tsong-Li Wang; Dennis E. Shasha (Int. J. Found. Comput. Sci., 1996)

Information Extraction from the Structured Part of Office Documents. - Xiaolong Hao; Jason Tsong-Li Wang; Peter A. Ng (Inf. Sci., 1996)

Curriculum Knowledge Representation and Manipulation in Knowledge-Based Tutoring Systems. - Gang Zhou; Jason Tsong-Li Wang; Peter A. Ng (IEEE Trans. Knowl. Data Eng., 1996)

A graphical environment for change detection in structured documents. - George Jyh-Shian Chang; Girish Patel; Liam Relihan; Jason Tsong-Li Wang (COMPSAC, 1997)

Electronic enterprise engineering: an outline of an architecture. - Michael Bieber; Michael R. Bartolacci; Jerry Fjermestad; Franz J. Kurfess; Qianhong Liu; Marvin K. Nakayama; Ajaz Rana; Wilhelm R. Rossak; Richard B. Scherl; Murat M. Tanik; Jason Tsong-Li Wang; Raymond T. Yeh; et al. (ECBS, 1997)

Scientific Data Classification: A Case Study. - Gung-Wei Chirn; Jason Tsong-Li Wang; Zhiyuan Wang (ICTAI, 1997)

Automated Discovery of Active Motifs in Three Dimensional Molecules. - Xiong Wang; Jason Tsong-Li Wang; Dennis E. Shasha; Bruce A. Shapiro; Sitaram Dikshitulu; Isidore Rigoutsos; Kaizhong Zhang (KDD, 1997)

Structural Matching and Discovery in Document Databases. - Jason Tsong-Li Wang; Dennis E. Shasha; George Jyh-Shian Chang; Liam Relihan; Kaizhong Zhang; Girish Patel (SIGMOD Conference, 1997)

Knowledge Discovering for Document Classification Using Tree Matching in TEXPROS. - Ching-Song Wei; Qianhong Liu; Jason Tsong-Li Wang; Peter A. Ng (Inf. Sci., 1997)

Fast retrieval of electronic messages that contain mistyped words or spelling errors. - Jason Tsong-Li Wang; Chia-Yo Chang (IEEE Trans. Syst. Man Cybern. Part B, 1997)

An Approximate Oracle for Distance in Metric Spaces. - Yanling Yang; Kaizhong Zhang; Xiong Wang; Jason Tsong-Li Wang; Dennis E. Shasha (CPM, 1998)

Fast similarity search in databases of 3D objects. - Xiong Wang; Jason Tsong-Li Wang (ICTAI, 1998)

Scientific Data Mining: A Case Study. - Chia-Yo Chang; Jason Tsong-Li Wang; Roger K. Chang (Int. J. Softw. Eng. Knowl. Eng., 1998)

An Algorithm for Finding the Largest Approximately Common Substructures of Two Trees. - Jason Tsong-Li Wang; Bruce A. Shapiro; Dennis E. Shasha; Kaizhong Zhang; Kathleen M. Currey (IEEE Trans. Pattern Anal. Mach. Intell., 1998)

A Framework for Biological Pattern Discovery on Networks of Workstations. - Bin Li 090; Dennis E. Shasha; Jason Tsong-Li Wang (Pattern Discovery in Biomolecular Data, 1999)

Pattern Discovery and Classification in Biosequences. - Jason Tsong-Li Wang; Thomas G. Marr; Steve Rozen; Dennis E. Shasha (Pattern Discovery in Biomolecular Data, 1999)

Application of Bayesian Neural Networks to Protein Sequence Classification. - Qicheng Ma; Jason Tsong-Li Wang (IC-AI, 1999)

Evaluating a Class of Distance-Mapping Algorithms for Data Mining and Clustering. - Jason Tsong-Li Wang; Xiong Wang; King-Ip (David) Lin; Dennis E. Shasha; Bruce A. Shapiro; Kaizhong Zhang (KDD, 1999)

Biocomputing - Introduction to the Special Issue. - James R. Gattiker; Jason Tsong-Li Wang (Int. J. Artif. Intell. Tools, 1999)

Biological Data Mining Using Bayesian Neural Networks: A Case Study. - Qicheng Ma; Jason Tsong-Li Wang (Int. J. Artif. Intell. Tools, 1999)

Identifying Approximately Common Substructures in Trees Based on a Restricted Edit Distance. - Jason Tsong-Li Wang; Kaizhong Zhang; Chia-Yo Chang (Inf. Sci., 1999)

New Techniques for DNA Sequence Classification. - Jason Tsong-Li Wang; Steve Rozen; Bruce A. Shapiro; Dennis E. Shasha; Zhiyuan Wang; Maisheng Yin (J. Comput. Biol., 1999)

Application of hidden Markov models to biological data mining: a case study. - Michael M. Yin; Jason T. L. Wang (Data Mining and Knowledge Discovery: Theory, Tools, and Technology, 2000)

Application of neural networks to biological data mining: a case study in protein sequence classification. - Jason Tsong-Li Wang; Qicheng Ma; Dennis E. Shasha; Cathy H. Wu (KDD, 2000)

An Approximate Search Engine for Structural Databases. - Jason Tsong-Li Wang; Xiong Wang; Dennis E. Shasha; Bruce A. Shapiro; Kaizhong Zhang; Xinhuan Zheng; Qicheng Ma; Zasha Weinberg (SIGMOD Conference, 2000)

Identifying consensus of trees through alignment. - Jason Tsong-Li Wang; Kaizhong Zhang (Inf. Sci., 2000)

Fast Similarity Search in Three-Dimensional Structure Databases. - Xiong Wang; Jason Tsong-Li Wang (J. Chem. Inf. Comput. Sci., 2000)

An Index Structure for Data Mining and Clustering. - Xiong Wang; Jason Tsong-Li Wang; King-Ip (David) Lin; Dennis E. Shasha; Bruce A. Shapiro; Kaizhong Zhang (Knowl. Inf. Syst., 2000)

Mining the World Wide Web: An Information Search Approach - George Jyh-Shian Chang; Marcus J. Healey; James A. M. McHugh; Jason Tsong-Li Wang (Kluwer, 2001)

New techniques for extracting features from protein sequences. - Jason Tsong-Li Wang; Qicheng Ma; Dennis E. Shasha; Cathy H. Wu (IBM Syst. J., 2001)

Bioinformatics - Introduction to the Special Issue. - James R. Gattiker; Jason Tsong-Li Wang; Paul P. Wang (Inf. Sci., 2001)

Effective hidden Markov models for detecting splicing junction sites in DNA sequences. - Michael M. Yin; Jason Tsong-Li Wang (Inf. Sci., 2001)

Precise Environmental Searches: Integrating Hierarchical Information Search with EnviroDaemon. - George Jyh-Shian Chang; Gunjan Samtani; Marcus L. Healey; Franz J. Kurfess; Jason Tsong-Li Wang (J. Syst. Integr., 2001)

Finding similar consensus between trees: an algorithm and a distance hierarchy. - Jason Tsong-Li Wang; Kaizhong Zhang (Pattern Recognit., 2001)

DNA sequence classification via an expectation maximization algorithm and neural networks: a case study. - Qicheng Ma; Jason Tsong-Li Wang; Dennis E. Shasha; Cathy H. Wu (IEEE Trans. Syst. Man Cybern. Part C, 2001)

Mining Genes in DNA Using GeneScout. - Michael M. Yin; Jason Tsong-Li Wang (ICDM, 2002)

Foreword. - Mohammed Javeed Zaki; Jason Tsong-Li Wang; Hannu Toivonen (BIOKDD, 2002)

Clustering and Classifying Enzymes in Metabolic Pathways: Some Preliminary Results. - Sen Zhang 007; Li Liao; Jean-François Tomb; Jason Tsong-Li Wang (BIOKDD, 2002)

Algorithmics and Applications of Tree and Graph Searching. - Dennis E. Shasha; Jason Tsong-Li Wang; Rosalba Giugno (PODS, 2002)

A Structure-Based Search Engine for Phylogenetic Databases. - Huiyuan Shan; Katherine G. Herbert; William H. Piel; Dennis E. Shasha; Jason Tsong-Li Wang (SSDBM, 2002)

ATreeGrep: Approximate Searching in Unordered Trees. - Dennis E. Shasha; Jason Tsong-Li Wang; Huiyuan Shan; Kaizhong Zhang (SSDBM, 2002)

XML Query by Example. - Sen Zhang 007; Jason Tsong-Li Wang; Katherine G. Herbert (Int. J. Comput. Intell. Appl., 2002)

Finding approximate patterns in undirected acyclic graphs. - Jason Tsong-Li Wang; Kaizhong Zhang; George Jyh-Shian Chang; Dennis E. Shasha (Pattern Recognit., 2002)

BIOKDD01: Workshop on Data Mining in Bioinformatics. - Mohammed Javeed Zaki; Jason Tsong-Li Wang; Hannu Toivonen (SIGKDD Explor., 2002)

BIOKDD 2002: Recent Advanced in Data Minig for Bioinformatics. - Mohammed Javeed Zaki; Jason Tsong-Li Wang; Hannu Toivonen (SIGKDD Explor., 2002)

Finding Patterns in Three-Dimensional Graphs: Algorithms and Applications to Scientific Data Mining. - Xiong Wang; Jason Tsong-Li Wang; Dennis E. Shasha; Bruce A. Shapiro; Isidore Rigoutsos; Kaizhong Zhang (IEEE Trans. Knowl. Data Eng., 2002)

Protein Classification: A Geometric Hashing Approach. - Xiong Wang; Jason Tsong-Li Wang (Computational Biology and Genome Informatics, 2003)

Opening Remarks. - Mohammed Javeed Zaki; Jason Tsong-Li Wang; Hannu Toivonen (BIOKDD, 2003)

TreeRank: A Similarity Measure for Nearest Neighbor Searching in Phylogenetic Databases. - Jason Tsong-Li Wang; Huiyuan Shan; Dennis E. Shasha; William H. Piel (SSDBM, 2003)

Special issue on data management in bioinformatics. - Mohammed Javeed Zaki; Jason Tsong-Li Wang (Inf. Syst., 2003)

Data mining in bioinformatics: report on BIOKDD'03. - Mohammed Javeed Zaki; Jason Tsong-Li Wang; Hannu Toivonen (SIGKDD Explor., 2003)

Unordered Tree Mining with Applications to Phylogeny. - Dennis E. Shasha; Jason Tsong-Li Wang; Sen Zhang 007 (ICDE, 2004)

XML Clustering by Principal Component Analysis. - Jianghui Liu; Jason T. L. Wang; Wynne Hsu; Katherine G. Herbert (ICTAI, 2004)

FlowMiner: Finding Flow Patterns in Spatio-Temporal Databases. - Junmei Wang; Wynne Hsu; Mong-Li Lee; Jason Tsong-Li Wang (ICTAI, 2004)

GeneScout: a data mining system for predicting vertebrate genes in genomic DNA sequences. - Michael M. Yin; Jason Tsong-Li Wang (Inf. Sci., 2004)

BIO-AJAX: An Extensible Framework for Biological Data Cleaning. - Katherine G. Herbert; Narain H. Gehani; William H. Piel; Jason Tsong-Li Wang; Cathy H. Wu (SIGMOD Rec., 2004)

Introduction to Data Mining in Bioinformatics. - Jason Tsong-Li Wang; Mohammed Javeed Zaki; Hannu Toivonen; Dennis E. Shasha (Data Mining in Bioinformatics, 2005)

Biomonitoring, Phylogenetics and Anomaly Aggregation Systems. - David R. B. Stockwell; Jason T. L. Wang (ISI, 2005)

Lineage Path Integration for Phylogenetic Resources. - Katherine G. Herbert; Shashikanth Pusapati; Jason Tsong-Li Wang; William H. Piel (SSDBM, 2005)

A method for aligning RNA secondary structures and its application to RNA motif detection. - Jianghui Liu; Jason Tsong-Li Wang; Jun Hu; Bin Tian 002 (BMC Bioinform., 2005)

Xml Clustering And Retrieval Through Principal Component Analysis. - Jason T. L. Wang; Jianghui Liu; Junhan Wang (Int. J. Artif. Intell. Tools, 2005)

MetricMap: an embedding technique for processing distance-based queries in metric spaces. - Jason Tsong-Li Wang; Xiong Wang; Dennis E. Shasha; Kaizhong Zhang (IEEE Trans. Syst. Man Cybern. Part B, 2005)

RADAR: An InteractiveWeb-Based Toolkit for RNA Data Analysis and Research. - Mugdha Khaladkar; Vivian Bellofatto; Jason T. L. Wang; Bin Tian 002; Kaizhong Zhang (BIBE, 2006)

A New Kernel Method for RNA Classification. - Xiaoming Wu; Jason Tsong-Li Wang; Katherine G. Herbert (BIBE, 2006)

Mining Frequent Agreement Subtrees in Phylogenetic Databases. - Sen Zhang 007; Jason Tsong-Li Wang (SDM, 2006)

PhyloMiner: A Tool for Evolutionary Data Analysis. - Sen Zhang 007; Katherine G. Herbert; Jason T. L. Wang; William H. Piel; David R. B. Stockwell (SSDBM, 2006)

Kernel design for RNA classification using Support Vector Machines. - Jason T. L. Wang; Xiaoming Wu (Int. J. Data Min. Bioinform., 2006)

Classification of RNA Sequences with Support Vector Machines. - Jason T. L. Wang; Xiaoming Wu (Analysis of Biological Data: A Soft Computing Approach, 2007)

Constrained RNA Structural Alignment: Algorithms and Application to Motif Detection in the Untranslated Regions of Trypanosoma brucei mRNAs. - Mugdha Khaladkar; Vivian Bellofatto; Jason Tsong-Li Wang; Vandanaben Patel; Marvin K. Nakayama (BIBE, 2007)

A New Algorithm for RNA Secondary Structure Prediction. - Junilda Spirollari; Jason T. L. Wang; Yongkyu Park (BIOCOMP, 2007)

Detecting Conserved RNA Secondary Structures in Viral Genomes: The RADAR Approach. - Mugdha Khaladkar; Jason T. L. Wang (BioSurveillance, 2007)

Toward an Integrated RNA Motif Database. - Jason Tsong-Li Wang; Dongrong Wen; Bruce A. Shapiro; Katherine G. Herbert; Jing Li; Kaushik Ghosh (DILS, 2007)

A study of phylogenetic tools for genomic nomenclature data cleaning. - Jonathan D. Marra; Katherine G. Herbert; Jason T. L. Wang (ITiCSE, 2007)

Biological data cleaning: a case study. - Katherine G. Herbert; Jason T. L. Wang (Int. J. Inf. Qual., 2007)

RADAR: a web server for RNA data analysis and research. - Mugdha Khaladkar; Vivian Bellofatto; Jason Tsong-Li Wang; Bin Tian 002; Bruce A. Shapiro (Nucleic Acids Res., 2007)

Detecting conserved secondary structures in RNA molecules using constrained structural alignment. - Mugdha Khaladkar; Vandanaben Patel; Vivian Bellofatto; Jeffrey Wilusz; Jason Tsong-Li Wang (Comput. Biol. Chem., 2008)

Discovering Frequent Agreement Subtrees from Phylogenetic Data. - Sen Zhang 007; Jason Tsong-Li Wang (IEEE Trans. Knowl. Data Eng., 2008)

Bioinformatic Databases. - Katherine G. Herbert; Junilda Spirollari; Jason Tsong-Li Wang; William H. Piel; John D. Westbrook; Winona C. Barker; Zhang-Zhi Hu; Cathy H. Wu (Wiley Encyclopedia of Computer Science and Engineering, 2008)

Bioinformatics Methods for Studying MicroRNA and ARE-Mediated Regulation of Post-Transcriptional Gene Expression. - Richipal Singh Bindra; Jason T. L. Wang; Paramjeet Singh Bagga (Int. J. Knowl. Discov. Bioinform., 2010)

On Comparing Two Structured RNA Multiple alignments. - Vandanaben Patel; Jason T. L. Wang; Shefali Setia; Anurag Verma; Charles D. Warden; Kaizhong Zhang (J. Bioinform. Comput. Biol., 2010)

In silico prediction of noncoding RNAs using supervised learning and feature ranking methods. - Stephen J. Griesmer; Miguel Cervantes-Cervantes; Yang Song; Jason T. L. Wang (Int. J. Bioinform. Res. Appl., 2011)

Genome-wide search for coaxial helical stacking motifs. - Kevin Byron; Jason T. L. Wang; Dongrong Wen (BIBE, 2012)

Pre-miRNA classification via combinatorial feature mining and boosting. - Ling Zhong; Jason T. L. Wang; Dongrong Wen; Bruce A. Shapiro (BIBM, 2012)

Searching for Non-coding RNAs in Genomic Sequences Using ncRNAscout. - Michael Bao; Miguel Cervantes-Cervantes; Ling Zhong; Jason T. L. Wang (Genom. Proteom. Bioinform., 2012)

A Method for Discovering Common Patterns from Two RNA Secondary Structures and its Application to Structural Repeat Detection. - Lei Hua; Jason T. L. Wang; Xiang Ji; Ankur Malhotra; Mugdha Khaladkar; Bruce A. Shapiro; Kaizhong Zhang (J. Bioinform. Comput. Biol., 2012)

Fast Elastic Peak Detection for Mass Spectrometry Data Mining. - Xin Zhang 095; Dennis E. Shasha; Yang Song; Jason T. L. Wang (IEEE Trans. Knowl. Data Eng., 2012)

Novel features for identifying A-minors in three-dimensional RNA molecules. - Palak Sheth; Miguel Cervantes-Cervantes; Akhila Nagula; Christian Laing; Jason T. L. Wang (Comput. Biol. Chem., 2013)

Genome-Wide Prediction of Coaxial Helical Stacking Using Random Forests and Covariance Models. - Kevin Byron; Jason T. L. Wang; Dongrong Wen (Int. J. Artif. Intell. Tools, 2014)

A New Approach to Link Prediction in Gene Regulatory Networks. - Turki Turki; Jason T. L. Wang (IDEAL, 2015)

Effective alignment of RNA pseudoknot structures using partition function posterior log-odds scores. - Yang Song; Lei Hua; Bruce A. Shapiro; Jason Tsong-Li Wang (BMC Bioinform., 2015)

New Techniques for Mining Frequent Patterns in Unordered Trees. - Sen Zhang 007; Zhihui Du; Jason Tsong-Li Wang (IEEE Trans. Cybern., 2015)

Bioinformatics Database Systems. - Kevin Byron; Katherine G. Herbert; Jason T. L. Wang (CRC Press, 2016)

Inferring Gene Regulatory Networks by Combining Supervised and Unsupervised Methods. - Turki Turki; Jason T. L. Wang; Ibrahim Rajikhan (ICMLA, 2016)

A Learning Framework to Improve Unsupervised Gene Network Inference. - Turki Turki; William Bassett; Jason T. L. Wang (MLDM, 2016)

CHSalign: A Web Server That Builds upon Junction-Explorer and RNAJAG for Pairwise Alignment of RNA Secondary Structures with Coaxial Helical Stacking. - Lei Hua; Yang Song; Namhee Kim; Christian Laing; Jason T. L. Wang; Tamar Schlick (CoRR, 2016)

Semi-Supervised Prediction of Gene Regulatory Networks Using Machine Learning Algorithms. - Nihir Patel; Jason T. L. Wang (CoRR, 2016)

Effective Classification of MicroRNA Precursors Using Combinatorial Feature Mining and AdaBoost Algorithms. - Ling Zhong; Jason T. L. Wang (CoRR, 2016)

A Time-Delayed Information-Theoretic Approach to the Reverse Engineering of Gene Regulatory Networks Using Apache Spark. - Yasser Abduallah; Jason T. L. Wang (DASC/PiCom/DataCom/CyberSciTech, 2017)

Reverse Engineering Regulatory Networks in Cells Using a Dynamic Bayesian Network and Mutual Information Scoring Function. - Haodi Jiang; Turki Turki; Jason T. L. Wang (ICMLA, 2017)

Reverse Engineering Gene Regulatory Networks Using Sampling and Boosting Techniques. - Turki Turki; Jason Tsong-Li Wang (MLDM, 2017)

Transfer Learning Approaches to Improve Drug Sensitivity Prediction in Multiple Myeloma Patients. - Turki Turki; Zhi Wei 001; Jason T. L. Wang (IEEE Access, 2017)

MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach. - Yasser Abduallah; Turki Turki; Kevin Byron; Zongxuan Du; Miguel Cervantes-Cervantes; Jason T. L. Wang (CoRR, 2017)

A Computational Approach to Finding RNA Tertiary Motifs in Genomic Sequences. - Kevin Byron; Jason T. L. Wang (CoRR, 2017)

Guest Editorial: Special Section on Biological Data Mining and Its Applications in Healthcare. - Fei Wang 001; Xiaoli Li 001; Jason T. L. Wang; See-Kiong Ng (IEEE ACM Trans. Comput. Biol. Bioinform., 2017)

DLGraph: Malware Detection Using Deep Learning and Graph Embedding. - Haodi Jiang; Turki Turki; Jason T. L. Wang (ICMLA, 2018)

Reverse Engineering Gene Regulatory Networks Using Graph Mining. - Haodi Jiang; Turki Turki; Sen Zhang 007; Jason T. L. Wang (MLDM (1), 2018)

A 3D Atrous Convolutional Long Short-Term Memory Network for Background Subtraction. - Zhihang Hu; Turki Turki; NhatHai Phan; Jason T. L. Wang (IEEE Access, 2018)

Discovering frequent induced subgraphs from directed networks. - Sen Zhang 007; Zhihui Du; Jason T. L. Wang; Haodi Jiang (Intell. Data Anal., 2018)

A comparative review of recent bioinformatics tools for inferring gene regulatory networks using time-series expression data. - Kevin Byron; Jason T. L. Wang (Int. J. Data Min. Bioinform., 2018)

A transfer learning approach via procrustes analysis and mean shift for cancer drug sensitivity prediction. - Turki Turki; Zhi Wei 001; Jason T. L. Wang (J. Bioinform. Comput. Biol., 2018)

A Novel Adversarial Inference Framework for Video Prediction with Action Control. - Zhihang Hu; Jason Tsong-Li Wang (ICCV Workshops, 2019)

Generative Adversarial Networks for Video Prediction with Action Control. - Zhihang Hu; Jason T. L. Wang (IJCAI, 2019)

Clinical intelligence: New machine learning techniques for predicting clinical drug response. - Turki Turki; Jason T. L. Wang (Comput. Biol. Medicine, 2019)

Predicting Solar Flares Using a Long Short-Term Memory Network. - Hao Liu 025; Chang Liu 080; Jason T. L. Wang; Haimin Wang (CoRR, 2019)

New algorithms for inferring gene regulatory networks from time-series expression data on Apache Spark. - Yasser Abduallah; Jason T. L. Wang (Int. J. Big Data Intell., 2019)

Predicting Solar Flares Using a Long Short-term Memory Network. - Hao Liu 054; Chang Liu 080; Jason Tsong-Li Wang; Haimin Wang (Zenodo, 2019)

Predicting Solar Flares Using a Long Short-term Memory Network. - Hao Liu 054; Chang Liu 080; Jason Tsong-Li Wang; Haimin Wang (Zenodo, 2019)

Prism2/LSTM-flare-prediction: v1.0.1. - Hao Liu 054; Chang Liu 080; Jason Tsong-Li Wang; Haimin Wang (Zenodo, 2019)

Generative Adversarial Networks for Stochastic Video Prediction With Action Control. - Zhihang Hu; Turki Turki; Jason T. L. Wang (IEEE Access, 2020)

Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks. - Hao Liu 025; Chang Liu 080; Jason T. L. Wang; Haimin Wang (CoRR, 2020)

Inferring Vector Magnetic Fields from Stokes Profiles of GST/NIRIS Using a Convolutional Neural Network. - Hao Liu 025; Yan Xu 014; Jiasheng Wang; Ju Jing; Chang Liu 080; Jason T. L. Wang; Haimin Wang (CoRR, 2020)

Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations. - Gelu Nita; Manolis K. Georgoulis; Irina Kitiashvili; Viacheslav Sadykov; Enrico Camporeale; Alexander Kosovichev; Haimin Wang; Vincent Oria; Jason T. L. Wang; Rafal A. Angryk; Berkay Aydin; Azim Ahmadzadeh; et al. (CoRR, 2020)

Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning. - Haodi Jiang; Jiasheng Wang; Chang Liu 080; Ju Jing; Hao Liu 025; Jason T. L. Wang; Haimin Wang (CoRR, 2020)

DeepSun: Machine-Learning-as-a-Service for Solar Flare Prediction. - Yasser Abduallah; Jason T. L. Wang; Yang Nie; Chang Liu 080; Haimin Wang (CoRR, 2020)

Reconstruction of Total Solar Irradiance by Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Yucong Shen; Khalid A. Alobaid; Serena Criscuoli; Haimin Wang (FLAIRS, 2021)

Tracing Halpha Fibrils through Bayesian Deep Learning. - Haodi Jiang; Ju Jing; Jiasheng Wang; Chang Liu 080; Qin Li 020; Yan Xu 014; Jason T. L. Wang; Haimin Wang (CoRR, 2021)

Deep Learning Based Reconstruction of Total Solar Irradiance. - Yasser Abduallah; Jason T. L. Wang; Yucong Shen; Khalid A. Alobaid; Serena Criscuoli; Haimin Wang (CoRR, 2021)

Predicting Solar Flares with Machine Learning. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Predicting Solar Flares with Machine Learning. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Predicting Solar Flares with Machine Learning. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Predicting Solar Flares with Machine Learning. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning. - Haodi Jiang; Jiasheng Wang; Chang Liu 080; Ju Jing; Hao Liu 054; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning. - Haodi Jiang; Jiasheng Wang; Chang Liu 080; Ju Jing; Hao Liu 054; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning. - Haodi Jiang; Jiasheng Wang; Chang Liu 080; Ju Jing; Hao Liu 054; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks. - Hao Liu 054; Chang Liu 080; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Predicting Solar Flares Using a Long Short-term Memory Network. - Hao Liu 054; Chang Liu 080; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Predicting Solar Flares Using a Long Short-term Memory Network. - Hao Liu 054; Chang Liu 080; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks. - Hao Liu 054; Chang Liu 080; Jason T. L. Wang; Haimin Wang (Zenodo, 2021)

Forecasting the Disturbance Storm Time Index with Bayesian Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Prianka Bose; Genwei Zhang; Firas Gerges; Haimin Wang (FLAIRS, 2022)

A Novel Deep Learning Approach to the Statistical Downscaling of Temperatures for Monitoring Climate Change. - Firas Gerges; Michel C. Boufadel; Elie Bou-Zeid; Hani Nassif; Jason T. L. Wang (ICMLSC, 2022)

Early Prediction of Movie Success Using Machine Learning and Evolutionary Computation. - Firas Gerges; Danielle A. Azar; Joseph Vybihal; Jason T. L. Wang (ISCIT, 2022)

A Transformer-Based Framework for Geomagnetic Activity Prediction. - Yasser Abduallah; Jason T. L. Wang; Chunhui Xu 002; Haimin Wang (ISMIS, 2022)

A Novel Bayesian Deep Learning Approach to the Downscaling of Wind Speed with Uncertainty Quantification. - Firas Gerges; Michel C. Boufadel; Elie Bou-Zeid; Hani Nassif; Jason T. L. Wang (PAKDD (3), 2022)

Bayesian Multi-head Convolutional Neural Networks with Bahdanau Attention for Forecasting Daily Precipitation in Climate Change Monitoring. - Firas Gerges; Michel C. Boufadel; Elie Bou-Zeid; Ankit Darekar; Hani Nassif; Jason T. L. Wang (ECML/PKDD (5), 2022)

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. - Yasser Abduallah; Vania K. Jordanova; Hao Liu 025; Qin Li 020; Jason T. L. Wang; Haimin Wang (CoRR, 2022)

A Deep Learning Approach to Dst Index Prediction. - Yasser Abduallah; Jason T. L. Wang; Prianka Bose; Genwei Zhang; Firas Gerges; Haimin Wang (CoRR, 2022)

Inferring Line-of-Sight Velocities and Doppler Widths from Stokes Profiles of GST/NIRIS Using Stacked Deep Neural Networks. - Haodi Jiang; Qin Li 020; Yan Xu 014; Wynne Hsu; Kwangsu Ahn; Wenda Cao; Jason T. L. Wang; Haimin Wang (CoRR, 2022)

A Deep Learning Approach to Generating Photospheric Vector Magnetograms of Solar Active Regions for SOHO/MDI Using SDO/HMI and BBSO Data. - Haodi Jiang; Qin Li 020; Zhihang Hu; Nian Liu; Yasser Abduallah; Ju Jing; Genwei Zhang; Yan Xu 014; Wynne Hsu; Jason T. L. Wang; Haimin Wang (CoRR, 2022)

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. - Yasser Abduallah; Vania K. Jordanova; Hao Liu 054; Qin Li 020; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. - Yasser Abduallah; Vania K. Jordanova; Hao Liu 054; Qin Li 020; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. - Yasser Abduallah; Vania K. Jordanova; Hao Liu 054; Qin Li 020; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. - Yasser Abduallah; Vania K. Jordanova; Hao Liu 054; Qin Li 020; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. - Yasser Abduallah; Vania K. Jordanova; Hao Liu 054; Qin Li 020; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. - Yasser Abduallah; Vania K. Jordanova; Hao Liu 054; Qin Li 020; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network. - Yasser Abduallah; Vania K. Jordanova; Hao Liu 054; Qin Li 020; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Forecasting the Disturbance Storm Time Index with Bayesian Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Prianka Bose; Genwei Zhang; Firas Gerges; Haimin Wang (Zenodo, 2022)

Forecasting the Disturbance Storm Time Index with Bayesian Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Prianka Bose; Genwei Zhang; Firas Gerges; Haimin Wang (Zenodo, 2022)

Forecasting the Disturbance Storm Time Index with Bayesian Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Prianka Bose; Genwei Zhang; Firas Gerges; Haimin Wang (Zenodo, 2022)

Forecasting the Disturbance Storm Time Index with Bayesian Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Prianka Bose; Genwei Zhang; Firas Gerges; Haimin Wang (Zenodo, 2022)

Forecasting the Disturbance Storm Time Index with Bayesian Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Prianka Bose; Genwei Zhang; Firas Gerges; Haimin Wang (Zenodo, 2022)

Predicting Solar Flares with Machine Learning. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Reconstruction of Total Solar Irradiance by Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Yucong Shen; Khalid A. Alobaid; Serena Criscuoli; Haimin Wang (Zenodo, 2022)

A Transformer-Based Framework for Geomagnetic Activity Prediction. - Yasser Abduallah; Jason T. L. Wang; Chunhui Xu 002; Haimin Wang (Zenodo, 2022)

A Transformer-Based Framework for Geomagnetic Activity Prediction. - Yasser Abduallah; Jason T. L. Wang; Chunhui Xu 002; Haimin Wang (Zenodo, 2022)

A Transformer-Based Framework for Geomagnetic Activity Prediction. - Yasser Abduallah; Jason T. L. Wang; Chunhui Xu 002; Haimin Wang (Zenodo, 2022)

Predicting CME Arrival Time through Data Integration and Ensemble Learning. - Khalid A. Alobaid; Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting CME Arrival Time through Data Integration and Ensemble Learning. - Khalid A. Alobaid; Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting CME Arrival Time through Data Integration and Ensemble Learning. - Khalid A. Alobaid; Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting CME Arrival Time through Data Integration and Ensemble Learning. - Khalid A. Alobaid; Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Reconstruction of Total Solar Irradiance by Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Yucong Shen; Khalid A. Alobaid; Serena Criscuoli; Haimin Wang (Zenodo, 2022)

Reconstruction of Total Solar Irradiance by Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Yucong Shen; Khalid A. Alobaid; Serena Criscuoli; Haimin Wang (Zenodo, 2022)

Reconstruction of Total Solar Irradiance by Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Yucong Shen; Khalid A. Alobaid; Serena Criscuoli; Haimin Wang (Zenodo, 2022)

Reconstruction of Total Solar Irradiance by Deep Learning. - Yasser Abduallah; Jason T. L. Wang; Yucong Shen; Khalid A. Alobaid; Serena Criscuoli; Haimin Wang (Zenodo, 2022)

Tracing Hα Fibrils through Bayesian Deep Learning. - Haodi Jiang; Ju Jing; Jiasheng Wang; Chang Liu 080; Qin Li 020; Yan Xu 014; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Tracing Hα Fibrils through Bayesian Deep Learning. - Haodi Jiang; Ju Jing; Jiasheng Wang; Chang Liu 080; Qin Li 020; Yan Xu 014; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Tracing Hα Fibrils through Bayesian Deep Learning. - Haodi Jiang; Ju Jing; Jiasheng Wang; Chang Liu 080; Qin Li 020; Yan Xu 014; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks. - Haodi Jiang; Qin L; Yan Xu 014; Wynne Hsu; Kwangsu Ahn; Wenda Cao; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks. - Haodi Jiang; Qin Li 020; Yan Xu 014; Wynne Hsu; Kwangsu Ahn; Wenda Cao; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks. - Hao Liu 054; Chang Liu 080; Jason T. L. Wang; Haimin Wang (Zenodo, 2022)

Deep Learning-Enabled Prediction of Daily Solar Irradiance from Simulated Climate Data. - Firas Gerges; Michel C. Boufadel; Elie Bou-Zeid; Hani Nassif; Jason T. L. Wang (ICMLSC, 2023)

An Interpretable LSTM Network for Solar Flare Prediction. - Gautam Varma Datla; Haodi Jiang; Jason T. L. Wang (ICTAI, 2023)

Ensemble Learning for CME Arrival Time Prediction. - Khalid A. Alobaid; Jason T. L. Wang (CoRR, 2023)

Estimating Coronal Mass Ejection Mass and Kinetic Energy by Fusion of Multiple Deep-learning Models. - Khalid A. Alobaid; Yasser Abduallah; Jason T. L. Wang; Haimin Wang; Shen Fan; Jialiang Li; Huseyin Cavus; Vasyl Yurchyshyn (CoRR, 2023)

Deep Learning-Based Downscaling of Temperatures for Monitoring Local Climate Change Using Global Climate Simulation Data. - Firas Gerges; Michel C. Boufadel; Elie Bou-Zeid; Hani Nassif; Jason T. L. Wang (World Sci. Annu. Rev. Artif. Intell., 2023)

Predicting Solar Flares with Machine Learning. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang (Zenodo, 2023)

Tracing Hα Fibrils through Bayesian Deep Learning. - Haodi Jiang; Ju Jing; Jiasheng Wang; Chang Liu 080; Qin Li 020; Yan Xu 014; Jason T. L. Wang; Haimin Wang (Zenodo, 2023)

Tracing Hα Fibrils through Bayesian Deep Learning. - Haodi Jiang; Ju Jing; Jiasheng Wang; Chang Liu 080; Qin Li 020; Yan Xu 014; Jason T. L. Wang; Haimin Wang (Zenodo, 2023)

Tracing Hα Fibrils through Bayesian Deep Learning. - Haodi Jiang; Ju Jing; Jiasheng Wang; Chang Liu 080; Qin Li 020; Yan Xu 014; Jason T. L. Wang; Haimin Wang (Zenodo, 2023)

Tracing Hα Fibrils through Bayesian Deep Learning. - Haodi Jiang; Ju Jing; Jiasheng Wang; Chang Liu 080; Qin Li 020; Yan Xu 014; Jason T. L. Wang; Haimin Wang (Zenodo, 2023)

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks. - Haodi Jiang; Qin Li 020; Yan Xu 014; Wynne Hsu; Kwangsu Ahn; Wenda Cao; Jason T. L. Wang; Haimin Wang (Zenodo, 2023)

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks. - Haodi Jiang; Qin Li 020; Yan Xu 014; Wynne Hsu; Kwangsu Ahn; Wenda Cao; Jason T. L. Wang; Haimin Wang (Zenodo, 2023)

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks. - Haodi Jiang; Qin Li 020; Yan Xu 014; Wynne Hsu; Kwangsu Ahn; Wenda Cao; Jason T. L. Wang; Haimin Wang (Zenodo, 2023)

Stokes Inversion for GST/NIRIS Using Stacked Deep Neural Networks. - Haodi Jiang; Qin Li 020; Yan Xu 014; Wynne Hsu; Kwangsu Ahn; Wenda Cao; Jason T. L. Wang; Haimin Wang (Zenodo, 2023)

Operational prediction of solar flares using a transformer-based framework. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang; Yan Xu 014 (Zenodo, 2023)

Operational prediction of solar flares using a transformer-based framework. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang; Yan Xu 014 (Zenodo, 2023)

Operational prediction of solar flares using a transformer-based framework. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang; Yan Xu 014 (Zenodo, 2023)

Operational prediction of solar flares using a transformer-based framework. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang; Yan Xu 014 (Zenodo, 2023)

Operational prediction of solar flares using a transformer-based framework. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang; Yan Xu 014 (Zenodo, 2023)

Operational Prediction of Solar Flares Using a Transformer-Based Framework. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang; Yan Xu 014 (Zenodo, 2023)

An Interpretable Transformer Model for Operational Flare Forecasting. - Yasser Abduallah; Vinay Ram Gazula; Jason T. L. Wang (FLAIRS, 2024)

Multiclass Classification of Solar Flares in Imbalanced Data Using Ensemble Learning and Sampling Methods. - Haodi Jiang; Ryoma Matsuura; Jason T. L. Wang (FLAIRS, 2024)

Solar Image Synthesis with Generative Adversarial Networks. - Haodi Jiang; Jason T. L. Wang (ICMLA, 2024)

Interpretable Deep Learning for Solar Flare Prediction. - Vinay Ram Gazula; Katherine G. Herbert; Yasser Abduallah; Jason T. L. Wang (ICTAI, 2024)

Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification. - Yasser Abduallah; Khalid A. Alobaid; Jason T. L. Wang; Haimin Wang; Vania K. Jordanova; Vasyl Yurchyshyn; Huseyin Cavus; Ju Jing (CoRR, 2024)

Super-Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using SDO/HMI Data and an Attention-Aided Convolutional Neural Network. - Chunhui Xu 002; Jason T. L. Wang; Haimin Wang; Haodi Jiang; Qin Li 020; Yasser Abduallah; Yan Xu 014 (CoRR, 2024)

Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification. - Yasser Abduallah; Khalid A. Alobail; Jason T. L. Wang; Haimin Wang; Vania K. Jordanova; Vasyl Yurchyshyn; Huseyin Cavus; Ju Jing (Zenodo, 2024)

Long-term prediction of daily solar irradiance using Bayesian deep learning and climate simulation data. - Firas Gerges; Michel C. Boufadel; Elie Bou-Zeid; Hani Nassif; Jason T. L. Wang (Knowl. Inf. Syst., 2024)

Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification. - Yasser Abduallah; Khalid A. Alobail; Jason T. L. Wang; Haimin Wang; Vania K. Jordanova; Vasyl Yurchyshyn; Huseyin Cavus; Ju Jing (Zenodo, 2024)

Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification. - Yasser Abduallah; Khalid A. Alobail; Jason T. L. Wang; Haimin Wang; Vania K. Jordanova; Vasyl Yurchyshyn; Huseyin Cavus; Ju Jing (Zenodo, 2024)

Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification. - Yasser Abduallah; Khalid A. Alobail; Jason T. L. Wang; Haimin Wang; Vania K. Jordanova; Vasyl Yurchyshyn; Huseyin Cavus; Ju Jing (Zenodo, 2024)

Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification. - Yasser Abduallah; Khalid A. Alobail; Jason T. L. Wang; Haimin Wang; Vania K. Jordanova; Vasyl Yurchyshyn; Huseyin Cavus; Ju Jing (Zenodo, 2024)

Prediction of the SYM-H Index Using a Bayesian Deep Learning Method with Uncertainty Quantification. - Yasser Abduallah; Khalid A. Alobail; Jason T. L. Wang; Haimin Wang; Vania K. Jordanova; Vasyl Yurchyshyn; Huseyin Cavus; Ju Jing (Zenodo, 2024)

Downscaling daily wind speed with Bayesian deep learning for climate monitoring. - Firas Gerges; Michel C. Boufadel; Elie Bou-Zeid; Hani Nassif; Jason T. L. Wang (Int. J. Data Sci. Anal., 2024)

A transformer-based framework for predicting geomagnetic indices with uncertainty quantification. - Yasser Abduallah; Jason T. L. Wang; Haimin Wang; Ju Jing (J. Intell. Inf. Syst., 2024)

Explainable Artificial Intelligence in Deep Learning-Based Solar Storm Predictions. - Adam Rawashdeh; Jason T. L. Wang; Katherine G. Herbert (FLAIRS, 2025)

Prediction of Geoeffective CMEs Using SOHO Images and Deep Learning. - Khalid A. Alobaid; Jason T. L. Wang; Haimin Wang; Ju Jing; Yasser Abduallah; Zhenduo Wang; Hameedullah Farooki; Huseyin Cavus; Vasyl Yurchyshyn (CoRR, 2025)

An Interpretable Machine Learning Approach to Understanding the Relationships between Solar Flares and Source Active Regions. - Huseyin Cavus; Jason T. L. Wang; Teja P. S. Singampalli; Gani Caglar Coban; Hongyang Zhang; Abd-ur Raheem; Haimin Wang (CoRR, 2025)

Prediction of Halo Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and a Transformer Model. - Hongyang Zhang; Ju Jing; Jason T. L. Wang; Haimin Wang; Yasser Abduallah; Yan Xu 014; Khalid A. Alobaid; Hameedullah Farooki; Vasyl Yurchyshyn (CoRR, 2025)

Improving the Temporal Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using a Deep Generative Model. - Jialiang Li; Vasyl Yurchyshyn; Jason T. L. Wang; Haimin Wang; Yasser Abduallah; Khalid A. Alobaid; Chunhui Xu 002; Ruizhu Chen; Yan Xu 014 (CoRR, 2025)