Modifying kernels using label information improves SVM classification performance. - Martin Renqiang Min; Anthony J. Bonner; Zhaolei Zhang (ICMLA, 2007)

A Deep Non-linear Feature Mapping for Large-Margin kNN Classification. - Martin Renqiang Min; David A. Stanley; Zineng Yuan; Anthony J. Bonner; Zhaolei Zhang (ICDM, 2009)

Learning Random-Walk Kernels for Protein Remote Homology Identification and Motif Discovery. - Martin Renqiang Min; Rui Kuang; Anthony J. Bonner; Zhaolei Zhang (SDM, 2009)

Large-Margin kNN Classification Using a Deep Encoder Network - Martin Renqiang Min; David A. Stanley; Zineng Yuan; Anthony J. Bonner; Zhaolei Zhang (CoRR, 2009)

A Probabilistic Framework to Improve microRNA Target Prediction by Incorporating Proteomics Data. - Jingjing Li; Martin Renqiang Min; Anthony J. Bonner; Zhaolei Zhang (J. Bioinform. Comput. Biol., 2009)

Learned Random-Walk Kernels and Empirical-Map Kernels for Protein Sequence Classification. - Renqiang Min; Anthony J. Bonner; Jingjing Li; Zhaolei Zhang (J. Comput. Biol., 2009)

Deep Supervised t-Distributed Embedding. - Martin Renqiang Min; Laurens van der Maaten; Zineng Yuan; Anthony J. Bonner; Zhaolei Zhang (ICML, 2010)

Gene Expression Variability within and between Human Populations and Implications toward Disease Susceptibility. - Jingjing Li; Yu Liu 093; TaeHyung Kim; Renqiang Min; Zhaolei Zhang (PLoS Comput. Biol., 2010)

TIP: A probabilistic method for identifying transcription factor target genes from ChIP-seq binding profiles. - Chao Cheng; Renqiang Min; Mark Gerstein (Bioinform., 2011)

Machine Learning Approaches to Biological Sequence and Phenotype Data Analysis. - Renqiang Min (2011)

PhenoM: a database of morphological phenotypes caused by mutation of essential genes in Saccharomyces cerevisiae. - Ke Jin; Jingjing Li; Frederick S. Vizeacoumar; Zhijian Li; Renqiang Min; Lee Zamparo; Franco J. Vizeacoumar; Alessandro Datti; Brenda J. Andrews; Charles Boone; Zhaolei Zhang (Nucleic Acids Res., 2012)

Interpretable Sparse High-Order Boltzmann Machines. - Martin Renqiang Min; Xia Ning; Chao Cheng; Mark Gerstein (AISTATS, 2014)

Factorized sparse learning models with interpretable high order feature interactions. - Sanjay Purushotham; Martin Renqiang Min; C.-C. Jay Kuo; Rachel Ostroff (KDD, 2014)

An Integrated Approach To Blood-Based Cancer Diagnosis And Biomarker Discovery. - Martin Renqiang Min; Salim A. Chowdhury; Yanjun Qi; Alex Stewart; Rachel Ostroff (Pacific Symposium on Biocomputing, 2014)

Deep Semantic Embedding. - Hao Wu; Martin Renqiang Min; Bing Bai (SMIR@SIGIR, 2014)

High-order neural networks and kernel methods for peptide-MHC binding prediction. - Pavel P. Kuksa; Martin Renqiang Min; Rishabh Dugar; Mark Gerstein (Bioinform., 2015)

A Deep Learning Model for Structured Outputs with High-order Interaction. - Hongyu Guo; Xiaodan Zhu 001; Martin Renqiang Min (CoRR, 2015)

Automated IT system failure prediction: A deep learning approach. - Ke Zhang 013; Jianwu Xu; Martin Renqiang Min; Guofei Jiang; Konstantinos Pelechrinis; Hui Zhang 002 (IEEE BigData, 2016)

A Shallow High-Order Parametric Approach to Data Visualization and Compression. - Martin Renqiang Min; Hongyu Guo; Dongjin Song (CoRR, 2016)

Adaptive Feature Abstraction for Translating Video to Language. - Yunchen Pu; Martin Renqiang Min; Zhe Gan; Lawrence Carin (ICLR (Workshop), 2017)

Exemplar-centered Supervised Shallow Parametric Data Embedding. - Martin Renqiang Min; Hongyu Guo; Dongjin Song (IJCAI, 2017)

A Context-aware Attention Network for Interactive Question Answering. - Huayu Li; Martin Renqiang Min; Yong Ge; Asim Kadav (KDD, 2017)

Adaptive Convolutional Filter Generation for Natural Language Understanding. - Dinghan Shen; Martin Renqiang Min; Yitong Li 001; Lawrence Carin (CoRR, 2017)

Learning K-way D-dimensional Discrete Code For Compact Embedding Representations. - Ting Chen 007; Martin Renqiang Min; Yizhou Sun (CoRR, 2017)

Accelerating deep neural network training with inconsistent stochastic gradient descent. - Linnan Wang; Yi Yang 018; Renqiang Min; Srimat T. Chakradhar (Neural Networks, 2017)

Video Generation From Text. - Yitong Li 001; Martin Renqiang Min; Dinghan Shen; David E. Carlson; Lawrence Carin (AAAI, 2018)

Adaptive Feature Abstraction for Translating Video to Text. - Yunchen Pu; Martin Renqiang Min; Zhe Gan; Lawrence Carin (AAAI, 2018)

Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. - Dinghan Shen; Guoyin Wang 002; Wenlin Wang; Martin Renqiang Min; Qinliang Su; Yizhe Zhang 002; Chunyuan Li; Ricardo Henao; Lawrence Carin (ACL (1), 2018)

Learning Context-Aware Convolutional Filters for Text Processing. - Dinghan Shen; Martin Renqiang Min; Yitong Li 001; Lawrence Carin (EMNLP, 2018)

Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection. - Bo Zong; Qi Song; Martin Renqiang Min; Wei Cheng 002; Cristian Lumezanu; Dae-ki Cho; Haifeng Chen (ICLR (Poster), 2018)

Learning K-way D-dimensional Discrete Codes for Compact Embedding Representations. - Ting Chen 007; Martin Renqiang Min; Yizhou Sun (ICML, 2018)

Fully convolutional structured LSTM networks for joint 4D medical image segmentation. - Yang Gao 031; Jeff M. Phillips; Yan Zheng 001; Renqiang Min; P. Thomas Fletcher; Guido Gerig (ISBI, 2018)

Parametric t-Distributed Stochastic Exemplar-Centered Embedding. - Martin Renqiang Min; Hongyu Guo; Dinghan Shen (ECML/PKDD (1), 2018)

Optimal Transport Classifier: Defending Against Adversarial Attacks by Regularized Deep Embedding. - Yao Li 015; Martin Renqiang Min; Wenchao Yu; Cho-Jui Hsieh; Thomas C. M. Lee; Erik Kruus (CoRR, 2018)

On Novel Object Recognition: A Unified Framework for Discriminability and Adaptability. - Kai Li 012; Martin Renqiang Min; Bing Bai; Yun Fu 001; Hans Peter Graf (CIKM, 2019)

Rethinking Zero-Shot Learning: A Conditional Visual Classification Perspective. - Kai Li 012; Martin Renqiang Min; Yun Fu 001 (ICCV, 2019)

Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis. - Yogesh Balaji; Martin Renqiang Min; Bing Bai; Rama Chellappa; Hans Peter Graf (IJCAI, 2019)

Learning K-way D-dimensional Discrete Embedding for Hierarchical Data Visualization and Retrieval. - Xiaoyuan Liang; Martin Renqiang Min; Hongyu Guo; Guiling Wang 001 (IJCAI, 2019)

A Deep Spatio-Temporal Fuzzy Neural Network for Passenger Demand Prediction. - Xiaoyuan Liang; Guiling Wang 001; Martin Renqiang Min; Yi Qi; Zhu Han 001 (SDM, 2019)

Disentangled Deep Autoencoding Regularization for Robust Image Classification. - Zhenyu Duan; Martin Renqiang Min; Li Erran Li; Mingbo Cai; Yi Xu 001; Bingbing Ni (CoRR, 2019)

CNN-based Dual-Chain Models for Knowledge Graph Learning. - Bo Peng 009; Renqiang Min; Xia Ning (CoRR, 2019)

Improving Disentangled Text Representation Learning with Information-Theoretic Guidance. - Pengyu Cheng; Martin Renqiang Min; Dinghan Shen; Christopher Malon; Yizhe Zhang 002; Yitong Li 001; Lawrence Carin (ACL, 2020)

S3VAE: Self-Supervised Sequential VAE for Representation Disentanglement and Data Generation. - Yizhe Zhu; Martin Renqiang Min; Asim Kadav; Hans Peter Graf (CVPR, 2020)

Ranking-based Convolutional Neural Network Models for Peptide-MHC Binding Prediction. - Ziqi Chen; Martin Renqiang Min; Xia Ning (CoRR, 2020)

Molecule Optimization via Fragment-based Generative Models. - Ziqi Chen; Martin Renqiang Min; Srinivasan Parthasarathy 001; Xia Ning (CoRR, 2020)

Retrieval, Analogy, and Composition: A framework for Compositional Generalization in Image Captioning. - Zhan Shi; Hui Liu 033; Martin Renqiang Min; Christopher Malon; Li Erran Li; Xiaodan Zhu 001 (EMNLP (Findings), 2021)

Dual Projection Generative Adversarial Networks for Conditional Image Generation. - Ligong Han; Martin Renqiang Min; Anastasis Stathopoulos; Yu Tian 003; Ruijiang Gao; Asim Kadav; Dimitris N. Metaxas (ICCV, 2021)

Towards Robustness of Deep Neural Networks via Regularization. - Yao Li 015; Martin Renqiang Min; Thomas C. M. Lee; Wenchao Yu; Erik Kruus; Wei Wang 010; Cho-Jui Hsieh (ICCV, 2021)

Disentangled Recurrent Wasserstein Autoencoder. - Jun Han; Martin Renqiang Min; Ligong Han; Li Erran Li; Xuan Zhang (ICLR, 2021)

Hopper: Multi-hop Transformer for Spatiotemporal Reasoning. - Honglu Zhou; Asim Kadav; Farley Lai; Alexandru Niculescu-Mizil; Martin Renqiang Min; Mubbasir Kapadia; Hans Peter Graf (ICLR, 2021)

DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays. - Zhanlin Chen; Jing Zhang 062; Jason Liu 003; Yi Dai; Donghoon Lee 006; Martin Renqiang Min; Min Xu 009; Mark Gerstein (Bioinform., 2021)

A deep generative model for molecule optimization via one fragment modification. - Ziqi Chen; Martin Renqiang Min; Srinivasan Parthasarathy 001; Xia Ning (Nat. Mach. Intell., 2021)

StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis. - Zhiheng Li 002; Martin Renqiang Min; Kai Li 012; Chenliang Xu (CVPR, 2022)

Learning Transferable Reward for Query Object Localization with Policy Adaptation. - Tingfeng Li; Shaobo Han; Martin Renqiang Min; Dimitris N. Metaxas (ICLR, 2022)

T-Cell Receptor-Peptide Interaction Prediction with Physical Model Augmented Pseudo-Labeling. - Yiren Jian; Erik Kruus; Martin Renqiang Min (KDD, 2022)

AE-StyleGAN: Improved Training of Style-Based Auto-Encoders. - Ligong Han; Sri Harsha Musunuri; Martin Renqiang Min; Ruijiang Gao; Yu Tian 003; Dimitris N. Metaxas (WACV, 2022)

Source-Free Video Domain Adaptation with Spatial-Temporal-Historical Consistency Learning. - Kai Li 012; Deep Patel; Erik Kruus; Martin Renqiang Min (CVPR, 2023)

Conditional Image-to-Video Generation with Latent Flow Diffusion Models. - Haomiao Ni; Changhao Shi; Kai Li 012; Sharon X. Huang; Martin Renqiang Min (CVPR, 2023)

Exploring Compositional Visual Generation with Latent Classifier Guidance. - Changhao Shi; Haomiao Ni; Kai Li 012; Shaobo Han; Mingfu Liang; Martin Renqiang Min (CVPR Workshops, 2023)

Few-Shot Video Classification via Representation Fusion and Promotion Learning. - Haifeng Xia; Kai Li 012; Martin Renqiang Min; Zhengming Ding (ICCV, 2023)

Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering. - Tianxiao Li; Hongyu Guo; Filippo Grazioli; Mark Gerstein; Martin Renqiang Min (NeurIPS, 2023)

T-Cell Receptor Optimization with Reinforcement Learning and Mutation Polices for Precision Immunotherapy. - Ziqi Chen; Martin Renqiang Min; Hongyu Guo; Chao Cheng; Trevor Clancy; Xia Ning (RECOMB, 2023)

T-Cell Receptor Optimization with Reinforcement Learning and Mutation Policies for Precesion Immunotherapy. - Ziqi Chen; Martin Renqiang Min; Hongyu Guo; Chao Cheng; Trevor Clancy; Xia Ning (CoRR, 2023)

Attentive Variational Information Bottleneck for TCR-peptide interaction prediction. - Filippo Grazioli; Pierre Machart; Anja Mösch; Kai Li 012; Leonardo V. Castorina; Nico Pfeifer; Martin Renqiang Min (Bioinform., 2023)

Binding peptide generation for MHC Class I proteins with deep reinforcement learning. - Ziqi Chen; Baoyi Zhang; Hongyu Guo; Prashant S. Emani; Trevor Clancy; Chongming Jiang; Mark Gerstein; Xia Ning; Chao Cheng; Martin Renqiang Min (Bioinform., 2023)

Understanding Transcriptional Regulatory Redundancy by Learnable Global Subset Perturbations. - Junhao Liu 001; Siwei Xu; Dylan Riffle; Ziheng Duan; Martin Renqiang Min; Jing Zhang 062 (ACML, 2024)

Weakly-Supervised Temporal Action Localization with Multi-Modal Plateau Transformers. - Xin Hu; Kai Li 012; Deep Patel; Erik Kruus; Martin Renqiang Min; Zhengming Ding (CVPR Workshops, 2024)

Why Not Use Your Textbook? Knowledge-Enhanced Procedure Planning of Instructional Videos. - Kumaranage Ravindu Yasas Nagasinghe; Honglu Zhou; Malitha Gunawardhana; Martin Renqiang Min; Daniel Harari; Muhammad Haris Khan (CVPR, 2024)

Learning to Localize Actions in Instructional Videos with LLM-Based Multi-pathway Text-Video Alignment. - Yuxiao Chen 002; Kai Li 012; Wentao Bao; Deep Patel; Yu Kong 001; Martin Renqiang Min; Dimitris N. Metaxas (ECCV (82), 2024)

Exploring the Role of Reasoning Structures for Constructing Proofs in Multi-Step Natural Language Reasoning with Large Language Models. - Zi'ou Zheng; Christopher Malon; Martin Renqiang Min; Xiaodan Zhu 001 (EMNLP, 2024)

Predicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs. - Tianci Song; Eric Cosatto; Gaoyuan Wang; Rui Kuang; Mark Gerstein; Martin Renqiang Min; Jonathan Warrell (Bioinform., 2024)

Compositional 3D Scene Synthesis with Scene Graph Guided Layout-Shape Generation. - Yao Wei; Martin Renqiang Min; George Vosselman; Li Erran Li; Michael Ying Yang (CoRR, 2024)

DICE: Discrete Inversion Enabling Controllable Editing for Multinomial Diffusion and Masked Generative Models. - Xiaoxiao He; Ligong Han; Quan Dao; Song Wen 001; Minhao Bai; Di Liu 003; Han Zhang 010; Martin Renqiang Min; Felix Juefei-Xu; Chaowei Tan; Bo Liu 005; Kang Li 004; et al. (CoRR, 2024)

Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad. - Jonathan Warrell; Francesco Alesiani; Cameron Smith; Anja Mösch; Martin Renqiang Min (CoRR, 2024)

Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation. - Haoran Liu; Youzhi Luo; Tianxiao Li; James Caverlee; Martin Renqiang Min (AAAI, 2025)

Exploiting VLM Localizability and Semantics for Open Vocabulary Action Detection. - Wentao Bao; Kai Li 012; Yuxiao Chen 002; Deep Patel; Martin Renqiang Min; Yu Kong 001 (WACV, 2025)

Reducing Hallucinations of Medical Multimodal Large Language Models with Visual Retrieval-Augmented Generation. - Yun-Wei Chu; Kai Zhang; Christopher Malon; Martin Renqiang Min (CoRR, 2025)

Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach. - Haoxuan Chen; Yinuo Ren; Martin Renqiang Min; Lexing Ying; Zachary Izzo (CoRR, 2025)

PPDiff: Diffusing in Hybrid Sequence-Structure Space for Protein-Protein Complex Design. - Zhenqiao Song; Tiaoxiao Li; Lei Li; Martin Renqiang Min (CoRR, 2025)

Group Relative Augmentation for Data Efficient Action Detection. - Deep Anil Patel; Iain Melvin; Zachary Izzo; Martin Renqiang Min (CoRR, 2025)

Attribute-Centric Compositional Text-to-Image Generation. - Yuren Cong; Martin Renqiang Min; Li Erran Li; Bodo Rosenhahn; Michael Ying Yang (Int. J. Comput. Vis., 2025)