Evaluating influence diagrams with decision circuits. - Debarun Bhattacharjya; Ross D. Shachter (UAI, 2007)

Sensitivity analysis in decision circuits. - Debarun Bhattacharjya; Ross D. Shachter (UAI, 2008)

Three new sensitivity analysis methods for influence diagrams. - Debarun Bhattacharjya; Ross D. Shachter (UAI, 2010)

Dynamic programming in in uence diagrams with decision circuits. - Ross D. Shachter; Debarun Bhattacharjya (UAI, 2010)

From Reliability Block Diagrams to Fault Tree Circuits. - Debarun Bhattacharjya; Léa A. Deleris (Decis. Anal., 2012)

Formulating Asymmetric Decision Problems as Decision Circuits. - Debarun Bhattacharjya; Ross D. Shachter (Decis. Anal., 2012)

Towards effective business process availability management. - Rama Akkiraju; Debarun Bhattacharjya; Sammukh Gupta (J. Serv. Sci. Res., 2012)

A Big Data Approach to Computational Creativity. - Lav R. Varshney; Florian Pinel; Kush R. Varshney; Debarun Bhattacharjya; Angela Schörgendorfer; Yi-Min Chee (CoRR, 2013)

The Value of Information in Portfolio Problems with Dependent Projects. - Debarun Bhattacharjya; Jo Eidsvik; Tapan Mukerji (Decis. Anal., 2013)

Bayesian Interactive Decision Support for Multi-Attribute Problems with Even Swaps. - Debarun Bhattacharjya; Jeffrey O. Kephart (UAI, 2014)

The Value of Information in Some Variations of the Stopping Problem. - Debarun Bhattacharjya; Léa A. Deleris (Decis. Anal., 2014)

A Myopic Approach to OrderingNodes for Parameter Elicitationin Bayesian Belief Networks. - Debarun Bhattacharjya; Léa A. Deleris; Bonnie Ray (IEEE Trans. Knowl. Data Eng., 2014)

Track geometry defect rectification based on track deterioration modelling and derailment risk assessment. - Qing He 011; Hongfei Li; Debarun Bhattacharjya; Dhaivat Parikh; Arun Hampapur (J. Oper. Res. Soc., 2015)

Preference Models for Creative Artifacts and Systems. - Debarun Bhattacharjya (ICCC, 2016)

Statistical Analysis of Peer Detailing for Children's Diarrhea Treatments. - Yumeng Tao; Debarun Bhattacharjya; Aliza R. Heching; Aditya Vempaty; Moninder Singh; Felix Lam; Kush R. Varshney; Aleksandra Mojsilovic (AAAI Spring Symposia, 2017)

A cognitive assistant for risk identification and modeling. - Dharmashankar Subramanian; Debarun Bhattacharjya; Ruben Rodriguez Torrado; Jeffrey O. Kephart; Vijil Chenthamarakshan; Jesus Rios (IEEE BigData, 2017)

Effectiveness of peer detailing in a diarrhea program in Nigeria. - Yumeng Tao; Debarun Bhattacharjya; Aliza R. Heching; Aditya Vempaty; Moninder Singh; Felix Lam; Jan Houdek; M. Abubakar; Abdulwahab Alharbi; T. Braimoh; N. Ihebuzor; Aleksandra Mojsilovic; et al. (IBM J. Res. Dev., 2017)

Generalization across Contexts in Unsupervised Computational Creativity. - Dharmashankar Subramanian; Debarun Bhattacharjya; Lav R. Varshney (ICCC, 2018)

Proximal Graphical Event Models. - Debarun Bhattacharjya; Dharmashankar Subramanian; Tian Gao (NeurIPS, 2018)

Answering Binary Causal Questions Through Large-Scale Text Mining: An Evaluation Using Cause-Effect Pairs from Human Experts. - Oktie Hassanzadeh; Debarun Bhattacharjya; Mark Feblowitz; Kavitha Srinivas; Michael Perrone; Shirin Sohrabi; Michael Katz 001 (IJCAI, 2019)

A big data approach to computational creativity: The curious case of Chef Watson. - Lav R. Varshney; Florian Pinel; Kush R. Varshney; Debarun Bhattacharjya; Angela Schörgendorfer; Yi-Min Chee (IBM J. Res. Dev., 2019)

Event-Driven Continuous Time Bayesian Networks. - Debarun Bhattacharjya; Karthikeyan Shanmugam; Tian Gao; Nicholas Mattei; Kush R. Varshney; Dharmashankar Subramanian (AAAI, 2020)

A Multi-Channel Neural Graphical Event Model with Negative Evidence. - Tian Gao; Dharmashankar Subramanian; Karthikeyan Shanmugam; Debarun Bhattacharjya; Nicholas Mattei (AAAI, 2020)

GaSPing for Utility. - Mengyang Gu; Debarun Bhattacharjya; Dharmashankar Subramanian (AAAI, 2020)

Causal Knowledge Extraction through Large-Scale Text Mining. - Oktie Hassanzadeh; Debarun Bhattacharjya; Mark Feblowitz; Kavitha Srinivas; Michael Perrone; Shirin Sohrabi; Michael Katz 001 (AAAI, 2020)

Cause-Effect Association between Event Pairs in Event Datasets. - Debarun Bhattacharjya; Tian Gao; Nicholas Mattei; Dharmashankar Subramanian (IJCAI, 2020)

Order-Dependent Event Models for Agent Interactions. - Debarun Bhattacharjya; Tian Gao; Dharmashankar Subramanian (IJCAI, 2020)

State Variable Effects in Graphical Event Models. - Debarun Bhattacharjya; Dharmashankar Subramanian; Tian Gao (IJCAI, 2020)

Hawkesian Graphical Event Models. - Xiufan Yu; Karthikeyan Shanmugam; Debarun Bhattacharjya; Tian Gao; Dharmashankar Subramanian; Lingzhou Xue (PGM, 2020)

Value of Information Analysis for Complex Simulator Models: Application to Wind Farm Maintenance. - Hans Olav Vogt Myklebust; Jo Eidsvik; Iver Bakken Sperstad; Debarun Bhattacharjya (Decis. Anal., 2020)

Ordinal Historical Dependence in Graphical Event Models with Tree Representations. - Debarun Bhattacharjya; Tian Gao; Dharmashankar Subramanian (AAAI, 2021)

Causal Inference for Event Pairs in Multivariate Point Processes. - Tian Gao; Dharmashankar Subramanian; Debarun Bhattacharjya; Xiao Shou; Nicholas Mattei; Kristin P. Bennett (NeurIPS, 2021)

Process Independence Testing in Proximal Graphical Event Models. - Debarun Bhattacharjya; Karthikeyan Shanmugam; Tian Gao; Dharmashankar Subramanian (CLeaR, 2022)

IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data. - Tian Gao; Debarun Bhattacharjya; Elliot Nelson; Miao Liu 001; Yue Yu (ICML, 2022)

Summary Markov Models for Event Sequences. - Debarun Bhattacharjya; Saurabh Sihag; Oktie Hassanzadeh; Liza Bialik (IJCAI, 2022)

Knowledge-Based News Event Analysis and Forecasting Toolkit. - Oktie Hassanzadeh; Parul Awasthy; Ken Barker 002; Onkar Bhardwaj; Debarun Bhattacharjya; Mark Feblowitz; Lee Martie; Jian Ni; Kavitha Srinivas; Lucy Yip (IJCAI, 2022)

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

Hedging as Reward Augmentation in Probabilistic Graphical Models. - Debarun Bhattacharjya; Radu Marinescu 002 (NeurIPS, 2022)

Knowledge-Based News Event Analysis Toolkit. - Oktie Hassanzadeh; Parul Awasthy; Ken Barker 002; Onkar Bhardwaj; Debarun Bhattacharjya; Mark Feblowitz; Aamod Khatiwada; Lee Martie; Steve Fonin Mbouadeu; Jian Ni; Anik Saha; Sola Shirai; et al. (ISWC (Posters/Demos/Industry), 2022)

Rule-Based Link Prediction over Event-Related Causal Knowledge in Wikidata. - Sola S. Shirai; Aamod Khatiwada; Oktie Hassanzadeh; Debarun Bhattacharjya (Wikidata@ISWC, 2022)

Linearizing contextual bandits with latent state dynamics. - Elliot Nelson; Debarun Bhattacharjya; Tian Gao; Miao Liu 001; Djallel Bouneffouf 001; Pascal Poupart (UAI, 2022)

Score-Based Learning of Graphical Event Models with Background Knowledge Augmentation. - Debarun Bhattacharjya; Tian Gao; Dharmashankar Subramanian; Xiao Shou (AAAI, 2023)

Concurrent Multi-Label Prediction in Event Streams. - Xiao Shou; Tian Gao; Dharmashankar Subramanian; Debarun Bhattacharjya; Kristin P. Bennett (AAAI, 2023)

Influence-Aware Attention for Multivariate Temporal Point Processes. - Xiao Shou; Tian Gao; Dharmashankar Subramanian; Debarun Bhattacharjya; Kristin P. Bennett (CLeaR, 2023)

Weighted Clock Logic Point Process. - Ruixuan Yan; Yunshi Wen; Debarun Bhattacharjya; Ronny Luss; Tengfei Ma 001; Achille Fokoue; Anak Agung Julius (ICLR, 2023)

Probabilistic Attention-to-Influence Neural Models for Event Sequences. - Xiao Shou; Debarun Bhattacharjya; Tian Gao; Dharmashankar Subramanian; Oktie Hassanzadeh; Kristin P. Bennett (ICML, 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)

Probabilistic Rule Induction from Event Sequences with Logical Summary Markov Models. - Debarun Bhattacharjya; Oktie Hassanzadeh; Ronny Luss; Keerthiram Murugesan (IJCAI, 2023)

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

Pairwise Causality Guided Transformers for Event Sequences. - Xiao Shou; Debarun Bhattacharjya; Tian Gao; Dharmashankar Subramanian; Oktie Hassanzadeh; Kristin P. Bennett (NeurIPS, 2023)

A Case-Based Reasoning Approach to Knowledge-Based Event Prediction. - Sola Shirai; Debarun Bhattacharjya; Oktie Hassanzadeh (ISWC (Posters/Demos/Industry), 2023)

Event Prediction using Case-Based Reasoning over Knowledge Graphs. - Sola Shirai; Debarun Bhattacharjya; Oktie Hassanzadeh (WWW, 2023)

CHRONOS: A Schema-Based Event Understanding and Prediction System. - Maria Chang 001; Achille Fokoue; Rosario Uceda-Sosa; Parul Awasthy; Ken Barker 002; Sadhana Kumaravel; Oktie Hassanzadeh; Elton F. S. Soares; Tian Gao; Debarun Bhattacharjya; Radu Florian; Salim Roukos (AAAI, 2024)

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

Distilling Event Sequence Knowledge From Large Language Models. - Somin Wadhwa; Oktie Hassanzadeh; Debarun Bhattacharjya; Ken Barker 002; Jian Ni (ISWC (1), 2024)

Self-Supervised Contrastive Pre-Training for Multivariate Point Processes. - Xiao Shou; Dharmashankar Subramanian; Debarun Bhattacharjya; Tian Gao; Kristin P. Bennett (CoRR, 2024)

Foundation Model Sherpas: Guiding Foundation Models through Knowledge and Reasoning. - Debarun Bhattacharjya; Junkyu Lee 001; Don Joven Agravante; Balaji Ganesan; Radu Marinescu 002 (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)

Knowledge Base Construction for Knowledge-Augmented Text-to-SQL. - Jinheon Baek; Horst Samulowitz; Oktie Hassanzadeh; Dharmashankar Subramanian; Sola Shirai; Alfio Gliozzo; Debarun Bhattacharjya (ACL (Findings), 2025)

Q-function Decomposition with Intervention Semantics for Factored Action Spaces. - Junkyu Lee 001; Tian Gao; Elliot Nelson; Miao Liu 001; Debarun Bhattacharjya; Songtao Lu (AISTATS, 2025)

Shedding Light on Time Series Classification using Interpretability Gated Networks. - Yunshi Wen; Tengfei Ma 001; Ronny Luss; Debarun Bhattacharjya; Achille Fokoue; Anak Agung Julius (ICLR, 2025)

The Consistency Hypothesis in Uncertainty Quantification for Large Language Models. - Quan Xiao; Debarun Bhattacharjya; Balaji Ganesan; Radu Marinescu 002; Katsiaryna Mirylenka; Nhan H. Pham; Michael R. Glass; Junkyu Lee 001 (UAI, 2025)

FactReasoner: A Probabilistic Approach to Long-Form Factuality Assessment for Large Language Models. - Radu Marinescu 002; Debarun Bhattacharjya; Junkyu Lee 001; Tigran T. Tchrakian; Javier Carnerero-Cano; Yufang Hou 001; Elizabeth Daly; Alessandra Pascale (CoRR, 2025)

Less is More: Efficient Weight Farcasting with 1-Layer Neural Network. - Xiao Shou; Debarun Bhattacharjya; Yanna Ding; Chen Zhao; Rui Li; Jianxi Gao (CoRR, 2025)