Retrofitting Decision Tree Classifiers Using Kernel Density Estimation. - Padhraic Smyth; Alexander G. Gray; Usama M. Fayyad (ICML, 1995)

Automated Design of Quantum Circuits. - Colin P. Williams; Alexander G. Gray (QCQC, 1998)

An Integrated System for Multi-Rover Scientific Exploration. - Tara A. Estlin; Alexander G. Gray; Tobias Mann; Gregg R. Rabideau; Rebecca Castaño; Steve A. Chien; Eric Mjolsness (AAAI/IAAI, 1999)

'N-Body' Problems in Statistical Learning. - Alexander G. Gray; Andrew W. Moore 001 (NIPS, 2000)

Automatic Derivation of Statistical Algorithms: The EM Family and Beyond. - Alexander G. Gray; Bernd Fischer 002; Johann Schumann; Wray L. Buntine (NIPS, 2002)

Rapid Evaluation of Multiple Density Models. - Alexander G. Gray; Andrew W. Moore 001 (AISTATS, 2003)

New Algorithms for Efficient High Dimensional Non-parametric Classification. - Ting Liu 006; Andrew W. Moore 001; Alexander G. Gray (NIPS, 2003)

Nonparametric Density Estimation: Toward Computational Tractability. - Alexander G. Gray; Andrew W. Moore 001 (SDM, 2003)

An Investigation of Practical Approximate Nearest Neighbor Algorithms. - Ting Liu 006; Andrew W. Moore 001; Alexander G. Gray; Ke Yang 005 (NIPS, 2004)

Dual-Tree Fast Gauss Transforms. - Dongryeol Lee; Alexander G. Gray; Andrew W. Moore 001 (NIPS, 2005)

On-line anomaly detection of deployed software: a statistical machine learning approach. - George K. Baah; Alexander G. Gray; Mary Jean Harrold (SOQUA, 2006)

Faster Gaussian Summation: Theory and Experiment. - Dongryeol Lee; Alexander G. Gray (UAI, 2006)

New Algorithms for Efficient High-Dimensional Nonparametric Classification. - Ting Liu 006; Andrew W. Moore 001; Alexander G. Gray (J. Mach. Learn. Res., 2006)

Ultrafast Monte Carlo for Statistical Summations. - Michael P. Holmes; Alexander G. Gray; Charles Lee Isbell Jr. (NIPS, 2007)

Fast Nonparametric Conditional Density Estimation. - Michael P. Holmes; Alexander G. Gray; Charles L. Isbell Jr. (UAI, 2007)

Fast Mean Shift with Accurate and Stable Convergence. - Ping Wang 012; Dongryeol Lee; Alexander G. Gray; James M. Rehg (AISTATS, 2007)

Learning dissimilarities by ranking: from SDP to QP. - Hua Ouyang; Alexander G. Gray (ICML, 2008)

QUIC-SVD: Fast SVD Using Cosine Trees. - Michael P. Holmes; Alexander G. Gray; Charles Lee Isbell Jr. (NIPS, 2008)

Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method. - Dongryeol Lee; Alexander G. Gray (NIPS, 2008)

Massive-Scale Kernel Discriminant Analysis: Mining for Quasars. - Ryan Riegel; Alexander G. Gray; Gordon Richards (SDM, 2008)

Can great research be taught?: independent research with cross-disciplinary thinking and broader impact. - Nick Feamster; Alexander G. Gray (SIGCSE, 2008)

Learning Isometric Separation Maps - Nikolaos Vasiloglou; Alexander G. Gray; David V. Anderson (CoRR, 2008)

Submanifold density estimation. - Arkadas Ozakin; Alexander G. Gray (NIPS, 2009)

Linear-time Algorithms for Pairwise Statistical Problems. - Parikshit Ram; Dongryeol Lee; William B. March; Alexander G. Gray (NIPS, 2009)

Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions. - Parikshit Ram; Dongryeol Lee; Hua Ouyang; Alexander G. Gray (NIPS, 2009)

FuncICA for Time Series Pattern Discovery. - Nishant A. Mehta; Alexander G. Gray (SDM, 2009)

Non-negative Matrix Factorization, Convexity and Isometry. - Nikolaos Vasiloglou; Alexander G. Gray; David V. Anderson (SDM, 2009)

Detecting Spammers with SNARE: Spatio-temporal Network-level Automatic Reputation Engine. - Shuang Hao 001; Nadeem Ahmed Syed; Nick Feamster; Alexander G. Gray; Sven Krasser (USENIX Security Symposium, 2009)

Ovarian cancer detection from metabolomic liquid chromatography/mass spectrometry data by support vector machines. - Wei Guan 002; Manshui Zhou; Christina Y. Hampton; Benedict B. Benigno; L. DeEtte Walker; Alexander G. Gray; John F. McDonald 002; Facundo M. Fernández (BMC Bioinform., 2009)

Automatic joint classification and segmentation of whole cell 3D images. - Rajesh Narasimha; Hua Ouyang; Alexander G. Gray; Steven W. McLaughlin; Sriram Subramaniam (Pattern Recognit., 2009)

Stochastic Mirror Descent Algorithm for L1-Regularized Risk Minimizations. - Hua Ouyang; Alexander G. Gray (CIT, 2010)

Fast euclidean minimum spanning tree: algorithm, analysis, and applications. - William B. March; Parikshit Ram; Alexander G. Gray (KDD, 2010)

Automating Mathematical Program Transformations. - Ashish Agarwal; Sooraj Bhat; Alexander G. Gray; Ignacio E. Grossmann (PADL, 2010)

Fast Stochastic Frank-Wolfe Algorithms for Nonlinear SVMs. - Hua Ouyang; Alexander G. Gray (SDM, 2010)

Generative and Latent Mean Map Kernels - Nishant A. Mehta; Alexander G. Gray (CoRR, 2010)

Fast kernel conditional density estimation: A dual-tree Monte Carlo approach. - Michael P. Holmes; Alexander G. Gray; Charles Lee Isbell Jr. (Comput. Stat. Data Anal., 2010)

Toward interactive statistical modeling. - Sooraj Bhat; Ashish Agarwal; Alexander G. Gray; Richard W. Vuduc (ICCS, 2010)

Learning Protein Folding Energy Functions. - Wei Guan 002; Arkadas Ozakin; Alexander G. Gray; Jose Borreguero; Shashi Bhushan Pandit; Anna Jagielska; Liliana Wroblewska; Jeffrey Skolnick (ICDM, 2011)

Density estimation trees. - Parikshit Ram; Alexander G. Gray (KDD, 2011)

Semi-supervised hierarchy learning using multiple-labeled data. - Ailar Javadi; Alexander Gray 001; David Anderson; Visar Berisha (MLSP, 2011)

Data-Distributed Weighted Majority and Online Mirror Descent - Hua Ouyang; Alexander G. Gray (CoRR, 2011)

CAKE: Convex Adaptive Kernel Density Estimation. - Ravi Sastry Ganti Mahapatruni; Alexander G. Gray (AISTATS, 2011)

Introduction to astroML: Machine learning for astrophysics. - Jacob VanderPlas; Andrew J. Connolly; Zeljko Ivezic; Alexander G. Gray (CIDU, 2012)

Stochastic Smoothing for Nonsmooth Minimizations: Accelerating SGD by Exploiting Structure. - Hua Ouyang; Alexander G. Gray (ICML, 2012)

Fast algorithms for comprehensive n-point correlation estimates. - William B. March; Andrew J. Connolly; Alexander G. Gray (KDD, 2012)

NASA: achieving lower regrets and faster rates via adaptive stepsizes. - Hua Ouyang; Alexander G. Gray (KDD, 2012)

Maximum inner-product search using cone trees. - Parikshit Ram; Alexander G. Gray (KDD, 2012)

Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL. - Nishant A. Mehta; Dongryeol Lee; Alexander G. Gray (NIPS, 2012)

A type theory for probability density functions. - Sooraj Bhat; Ashish Agarwal; Richard W. Vuduc; Alexander G. Gray (POPL, 2012)

Optimizing the computation of n-point correlations on large-scale astronomical data. - William B. March; Kenneth Czechowski; Marat Dukhan; Thomas Benson; Dongryeol Lee; Andrew J. Connolly; Richard W. Vuduc; Edmond Chow; Alexander G. Gray (SC, 2012)

A Distributed Kernel Summation Framework for General-Dimension Machine Learning. - Dongryeol Lee; Richard W. Vuduc; Alexander G. Gray (SDM, 2012)

Nearest-Neighbor Search on a Time Budget via Max-Margin Trees. - Parikshit Ram; Dongryeol Lee; Alexander G. Gray (SDM, 2012)

Computer detection approaches for the identification of phasic electromyographic (EMG) activity during human sleep. - Jacqueline Fairley; George K. Georgoulas; Nishant A. Mehta; Alexander G. Gray; Donald L. Bliwise (Biomed. Signal Process. Control., 2012)

On the Sample Complexity of Predictive Sparse Coding - Nishant A. Mehta; Alexander G. Gray (CoRR, 2012)

Maximum Inner-Product Search using Tree Data-structures - Parikshit Ram; Alexander G. Gray (CoRR, 2012)

Stochastic ADMM for Nonsmooth Optimization - Hua Ouyang; Niao He; Alexander G. Gray (CoRR, 2012)

Multibody multipole methods. - Dongryeol Lee; Arkadas Ozakin; Alexander G. Gray (J. Comput. Phys., 2012)

UPAL: Unbiased Pool Based Active Learning. - Ravi Ganti; Alexander G. Gray (AISTATS, 2012)

Tree-Independent Dual-Tree Algorithms. - Ryan R. Curtin; William B. March; Parikshit Ram; David V. Anderson; Alexander G. Gray; Charles L. Isbell Jr. (ICML (3), 2013)

Sparsity-Based Generalization Bounds for Predictive Sparse Coding. - Nishant Ajay Mehta; Alexander G. Gray (ICML (1), 2013)

Stochastic Alternating Direction Method of Multipliers. - Hua Ouyang; Niao He; Long Q. Tran; Alexander G. Gray (ICML (1), 2013)

Which Space Partitioning Tree to Use for Search? - Parikshit Ram; Alexander G. Gray (NIPS, 2013)

Fast Exact Max-Kernel Search. - Ryan R. Curtin; Alexander G. Gray; Parikshit Ram (SDM, 2013)

Reduced Set KPCA for Improving the Training and Execution Speed of Kernel Machines. - Alexander G. Gray; Hassan A. Kingravi; Patricio A. Vela (SDM, 2013)

Building Bridges: Viewing Active Learning from the Multi-Armed Bandit Lens. - Ravi Ganti; Alexander G. Gray (UAI, 2013)

Local Support Vector Machines: Formulation and Analysis. - Ravi Ganti; Alexander G. Gray (CoRR, 2013)

Sparse high-dimensional fractional-norm support vector machine via DC programming. - Wei Guan 002; Alexander G. Gray (Comput. Stat. Data Anal., 2013)

Dependence maps, a dimensionality reduction with dependence distance for high-dimensional data. - Kichun Lee 001; Alexander G. Gray; Heeyoung Kim (Data Min. Knowl. Discov., 2013)

MLPACK: a scalable C++ machine learning library. - Ryan R. Curtin; James R. Cline; N. P. Slagle; William B. March; Parikshit Ram; Nishant A. Mehta; Alexander G. Gray (J. Mach. Learn. Res., 2013)

A distributed kernel summation framework for general-dimension machine learning. - Dongryeol Lee; Piyush Sao; Richard W. Vuduc; Alexander G. Gray (Stat. Anal. Data Min., 2014)

Fraud Detection with Density Estimation Trees. - Parikshit Ram; Alexander G. Gray (ADF@KDD, 2017)

Automated Machine Learning via ADMM. - Sijia Liu 001; Parikshit Ram; Djallel Bouneffouf 001; Gregory Bramble; Andrew R. Conn; Horst Samulowitz; Alexander G. Gray (CoRR, 2019)

How can AI Automate End-to-End Data Science? - Charu C. Aggarwal; Djallel Bouneffouf 001; Horst Samulowitz; Beat Buesser; Thanh Hoang; Udayan Khurana; Sijia Liu 001; Tejaswini Pedapati; Parikshit Ram; Ambrish Rawat; Martin Wistuba; Alexander G. Gray (CoRR, 2019)

AutoAIViz: Opening the Blackbox of Automated Artificial Intelligence with Conditional Parallel Coordinates. - Daniel Karl I. Weidele; Justin D. Weisz; Eno Oduor; Michael J. Muller; Josh Andres; Alexander G. Gray; Dakuo Wang (CoRR, 2019)

Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI. - Dakuo Wang; Justin D. Weisz; Michael J. Muller; Parikshit Ram; Werner Geyer; Casey Dugan; Yla R. Tausczik; Horst Samulowitz; Alexander G. Gray (Proc. ACM Hum. Comput. Interact., 2019)

An ADMM Based Framework for AutoML Pipeline Configuration. - Sijia Liu 001; Parikshit Ram; Deepak Vijaykeerthy; Djallel Bouneffouf 001; Gregory Bramble; Horst Samulowitz; Dakuo Wang; Andrew Conn 001; Alexander G. Gray (AAAI, 2020)

Survey on Automated End-to-End Data Science? - Djallel Bouneffouf 001; Charu C. Aggarwal; Thanh Hoang; Udayan Khurana; Horst Samulowitz; Beat Buesser; Sijia Liu 001; Tejaswini Pedapati; Parikshit Ram; Ambrish Rawat; Martin Wistuba; Alexander G. Gray (IJCNN, 2020)

AutoAIViz: opening the blackbox of automated artificial intelligence with conditional parallel coordinates. - Daniel Karl I. Weidele; Justin D. Weisz; Erick Oduor; Michael J. Muller; Josh Andres; Alexander G. Gray; Dakuo Wang (IUI, 2020)

Leveraging Semantic Parsing for Relation Linking over Knowledge Bases. - Nandana Mihindukulasooriya; Gaetano Rossiello; Pavan Kapanipathi; Ibrahim Abdelaziz; Srinivas Ravishankar; Mo Yu; Alfio Gliozzo; Salim Roukos; Alexander G. Gray (ISWC (1), 2020)

Solving Constrained CASH Problems with ADMM. - Parikshit Ram; Sijia Liu 001; Deepak Vijaykeerthy; Dakuo Wang; Djallel Bouneffouf 001; Gregory Bramble; Horst Samulowitz; Alexander G. Gray (CoRR, 2020)

Logical Neural Networks. - Ryan Riegel; Alexander G. Gray; Francois P. S. Luus; Naweed Khan; Ndivhuwo Makondo; Ismail Yunus Akhalwaya; Haifeng Qian; Ronald Fagin; Francisco Barahona; Udit Sharma; Shajith Ikbal; Hima Karanam; et al. (CoRR, 2020)

Foundations of Reasoning with Uncertainty via Real-valued Logics. - Ronald Fagin; Ryan Riegel; Alexander G. Gray (CoRR, 2020)

Question Answering over Knowledge Bases by Leveraging Semantic Parsing and Neuro-Symbolic Reasoning. - Pavan Kapanipathi; Ibrahim Abdelaziz; Srinivas Ravishankar; Salim Roukos; Alexander G. Gray; Ramón Fernandez Astudillo; Maria Chang 001; Cristina Cornelio; Saswati Dana; Achille Fokoue; Dinesh Garg; Alfio Gliozzo; et al. (CoRR, 2020)

A Semantic Parsing and Reasoning-Based Approach to Knowledge Base Question Answering. - Ibrahim Abdelaziz; Srinivas Ravishankar; Pavan Kapanipathi; Salim Roukos; Alexander G. Gray (AAAI, 2021)

LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking. - Hang Jiang; Sairam Gurajada; Qiuhao Lu; Sumit Neelam; Lucian Popa 001; Prithviraj Sen; Yunyao Li 001; Alexander G. Gray (ACL/IJCNLP (1), 2021)

Leveraging Abstract Meaning Representation for Knowledge Base Question Answering. - Pavan Kapanipathi; Ibrahim Abdelaziz; Srinivas Ravishankar; Salim Roukos; Alexander G. Gray; Ramón Fernandez Astudillo; Maria Chang 001; Cristina Cornelio; Saswati Dana; Achille Fokoue; Dinesh Garg; Alfio Gliozzo; et al. (ACL/IJCNLP (Findings), 2021)

LOA: Logical Optimal Actions for Text-based Interaction Games. - Daiki Kimura; Subhajit Chaudhury; Masaki Ono; Michiaki Tatsubori; Don Joven Agravante; Asim Munawar; Akifumi Wachi; Ryosuke Kohita; Alexander Gray 001 (ACL (demo), 2021)

A Semantics-aware Transformer Model of Relation Linking for Knowledge Base Question Answering. - Tahira Naseem; Srinivas Ravishankar; Nandana Mihindukulasooriya; Ibrahim Abdelaziz; Young-Suk Lee 001; Pavan Kapanipathi; Salim Roukos; Alfio Gliozzo; Alexander G. Gray (ACL/IJCNLP (2), 2021)

Neuro-Symbolic Reinforcement Learning with First-Order Logic. - Daiki Kimura; Masaki Ono; Subhajit Chaudhury; Ryosuke Kohita; Akifumi Wachi; Don Joven Agravante; Michiaki Tatsubori; Asim Munawar; Alexander Gray 001 (EMNLP (1), 2021)

Training Logical Neural Networks by Primal-Dual Methods for Neuro-Symbolic Reasoning. - Songtao Lu; Naweed Khan; Ismail Yunus Akhalwaya; Ryan Riegel; Lior Horesh; Alexander G. Gray (ICASSP, 2021)

Logic Embeddings for Complex Query Answering. - Francois P. S. Luus; Prithviraj Sen; Pavan Kapanipathi; Ryan Riegel; Ndivhuwo Makondo; Thabang Lebese; Alexander G. Gray (CoRR, 2021)

Reinforcement Learning with External Knowledge by using Logical Neural Networks. - Daiki Kimura; Subhajit Chaudhury; Akifumi Wachi; Ryosuke Kohita; Asim Munawar; Michiaki Tatsubori; Alexander Gray 001 (CoRR, 2021)

Combining Rules and Embeddings via Neuro-Symbolic AI for Knowledge Base Completion. - Prithviraj Sen; Breno W. S. R. Carvalho; Ibrahim Abdelaziz; Pavan Kapanipathi; Francois P. S. Luus; Salim Roukos; Alexander G. Gray (CoRR, 2021)

SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases. - Sumit Neelam; Udit Sharma; Hima Karanam; Shajith Ikbal; Pavan Kapanipathi; Ibrahim Abdelaziz; Nandana Mihindukulasooriya; Young-Suk Lee 001; Santosh K. Srivastava; Cezar Pendus; Saswati Dana; Dinesh Garg; et al. (CoRR, 2021)

Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks. - Prithviraj Sen; Breno W. S. R. de Carvalho; Ryan Riegel; Alexander G. Gray (AAAI, 2022)

X-FACTOR: A Cross-metric Evaluation of Factual Correctness in Abstractive Summarization. - Subhajit Chaudhury; Sarathkrishna Swaminathan; R. Chulaka Gunasekara; Maxwell Crouse; Srinivas Ravishankar; Daiki Kimura; Keerthiram Murugesan; Ramón Fernandez Astudillo; Tahira Naseem; Pavan Kapanipathi; Alexander Gray 001 (EMNLP, 2022)

SYGMA: A System for Generalizable and Modular Question Answering Over Knowledge Bases. - Sumit Neelam; Udit Sharma; Hima Karanam; Shajith Ikbal; Pavan Kapanipathi; Ibrahim Abdelaziz; Nandana Mihindukulasooriya; Young-Suk Lee 001; Santosh K. Srivastava; Cezar Pendus; Saswati Dana; Dinesh Garg; et al. (EMNLP (Findings), 2022)

Logical Neural Networks for Knowledge Base Completion with Embeddings & Rules. - Prithviraj Sen; Breno W. S. R. de Carvalho; Ibrahim Abdelaziz; Pavan Kapanipathi; Salim Roukos; Alexander G. Gray (EMNLP, 2022)

Zero-shot Entity Linking with Less Data. - G. P. Shrivatsa Bhargav; Dinesh Khandelwal; Saswati Dana; Dinesh Garg; Pavan Kapanipathi; Salim Roukos; Alexander G. Gray; L. Venkata Subramaniam (NAACL-HLT (Findings), 2022)

Logical Credal Networks. - Radu Marinescu 002; Haifeng Qian; Alexander G. Gray; Debarun Bhattacharjya; Francisco Barahona; Tian Gao; Ryan Riegel; Pravinda Sahu (NeurIPS, 2022)

A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases. - Sumit Neelam; Udit Sharma; Hima Karanam; Shajith Ikbal; Pavan Kapanipathi; Ibrahim Abdelaziz; Nandana Mihindukulasooriya; Young-Suk Lee 001; Santosh K. Srivastava; Cezar Pendus; Saswati Dana; Dinesh Garg; et al. (CoRR, 2022)

Learning Neuro-Symbolic World Models with Conversational Proprioception. - Don Joven Agravante; Daiki Kimura; Michiaki Tatsubori; Asim Munawar; Alexander Gray 001 (ACL (2), 2023)

Learning Symbolic Rules over Abstract Meaning Representations for Textual Reinforcement Learning. - Subhajit Chaudhury; Sarathkrishna Swaminathan; Daiki Kimura; Prithviraj Sen; Keerthiram Murugesan; Rosario Uceda-Sosa; Michiaki Tatsubori; Achille Fokoue; Pavan Kapanipathi; Asim Munawar; Alexander Gray 001 (ACL (1), 2023)

MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types. - Keerthiram Murugesan; Sarathkrishna Swaminathan; Soham Dan; Subhajit Chaudhury; R. Chulaka Gunasekara; Maxwell Crouse; Diwakar Mahajan; Ibrahim Abdelaziz; Achille Fokoue; Pavan Kapanipathi; Salim Roukos; Alexander Gray 001 (ACL (Findings), 2023)

Self-Supervised Rule Learning to Link Text Segments to Relational Elements of Structured Knowledge. - Shajith Ikbal; Udit Sharma; Hima Karanam; Sumit Neelam; Ronny Luss; Dheeraj Sreedhar; Pavan Kapanipathi; Naweed Khan; Kyle Erwin; Ndivhuwo Makondo; Ibrahim Abdelaziz; Achille Fokoue; et al. (EMNLP (Findings), 2023)

Approximate Inference in Logical Credal Networks. - Radu Marinescu 002; Haifeng Qian; Alexander G. Gray; Debarun Bhattacharjya; Francisco Barahona; Tian Gao; Ryan Riegel (IJCAI, 2023)

Credal Marginal MAP. - Radu Marinescu 002; Debarun Bhattacharjya; Junkyu Lee 001; Fábio G. Cozman; Alexander G. Gray (NeurIPS, 2023)

Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection. - Parikshit Ram; Alexander G. Gray; Horst C. Samulowitz; Gregory Bramble (SDM, 2023)

Towards a Unification of Logic and Information Theory. - Luis A. Lastras; Barry M. Trager; Jonathan Lenchner; Wojciech Szpankowski; Chai Wah Wu; Mark S. Squillante; Alexander Gray 001 (CoRR, 2023)

Scalable Learning of Latent Language Structure With Logical Offline Cycle Consistency. - Maxwell Crouse; Ramón Fernandez Astudillo; Tahira Naseem; Subhajit Chaudhury; Pavan Kapanipathi; Salim Roukos; Alexander Gray 001 (CoRR, 2023)

Compositional Program Generation for Systematic Generalization. - Tim Klinger; Luke Liu; Soham Dan; Maxwell Crouse; Parikshit Ram; Alexander Gray 001 (CoRR, 2023)

What Makes Models Compositional? A Theoretical View. - Parikshit Ram; Tim Klinger; Alexander G. Gray (IJCAI, 2024)

What makes Models Compositional? A Neuro-Symbolic Theoretical View (Extended Abstract). - Parikshit Ram; Tim Klinger; Alexander G. Gray (LNSAI@IJCAI, 2024)

Abductive Reasoning in Logical Credal Networks. - Radu Marinescu 002; Junkyu Lee 001; Debarun Bhattacharjya; Fábio G. Cozman; Alexander G. Gray (NeurIPS, 2024)

LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation. - Bowen Li 007; Zhaoyu Li; Qiwei Du; Jinqi Luo; Wenshan Wang; Yaqi Xie 001; Simon Stepputtis; Chen Wang 033; Katia P. Sycara; Pradeep Ravikumar; Alexander G. Gray; Xujie Si; et al. (NeurIPS, 2024)

A Neuro-Symbolic Approach to Multi-Agent RL for Interpretability and Probabilistic Decision Making. - Chitra Subramanian; Miao Liu; Naweed Khan; Jonathan Lenchner; Aporva Amarnath; Sarathkrishna Swaminathan; Ryan Riegel; Alexander Gray 001 (CoRR, 2024)

What makes Models Compositional? A Theoretical View: With Supplement. - Parikshit Ram; Tim Klinger; Alexander G. Gray (CoRR, 2024)

Markov conditions and factorization in logical credal networks. - Fábio G. Cozman; Radu Marinescu 002; Junkyu Lee 001; Alexander G. Gray; Ryan Riegel; Debarun Bhattacharjya (Int. J. Approx. Reason., 2024)

Neural Reasoning Networks: Efficient Interpretable Neural Networks with Automatic Textual Explanations. - Stephen Carrow; Kyle Erwin; Olga Vilenskaia; Parikshit Ram; Tim Klinger; Naweed Khan; Ndivhuwo Makondo; Alexander G. Gray (AAAI, 2025)

Dealing with cycles in graph-based probabilistic models: the case of Logical Credal Networks. - Fábio G. Cozman; Radu Marinescu 002; Junkyu Lee 001; Alexander Gray 001; Denis Deratani Mauá (ISIPTA, 2025)

Breaking through the classical Shannon entropy limit: A new frontier through logical semantics. - Luis A. Lastras; Barry M. Trager; Jonathan Lenchner; Wojciech Szpankowski; Chai Wah Wu; Mark S. Squillante; Alexander Gray 001 (CoRR, 2025)

Few-shot Policy (de)composition in Conversational Question Answering. - Kyle Erwin; Guy Axelrod; Maria Chang 001; Achille Fokoue; Maxwell Crouse; Soham Dan; Tian Gao; Rosario Uceda-Sosa; Ndivhuwo Makondo; Naweed Khan; Alexander G. Gray (CoRR, 2025)

Bilevel Learning for Bilevel Planning. - Bowen Li 007; Tom Silver; Sebastian A. Scherer; Alexander G. Gray (CoRR, 2025)

Transformers Learn Faster with Semantic Focus. - Parikshit Ram; Kenneth L. Clarkson; Tim Klinger; Shashanka Ubaru; Alexander G. Gray (CoRR, 2025)