Learning Bayes networks using interventional path queries in polynomial time and sample complexity. - Kevin Bello; Jean Honorio (CoRR, 2017)

Learning latent variable structured prediction models with Gaussian perturbations. - Kevin Bello; Jean Honorio (NeurIPS, 2018)

Computationally and statistically efficient learning of causal Bayes nets using path queries. - Kevin Bello; Jean Honorio (NeurIPS, 2018)

Improving Topic Coherence Using Entity Extraction Denoising. - Ronald Cardenas; Kevin Bello; Alberto Coronado; Elizabeth Villota (Prague Bull. Math. Linguistics, 2018)

Exact inference in structured prediction. - Kevin Bello; Jean Honorio (NeurIPS, 2019)

Minimax bounds for structured prediction. - Kevin Bello; Asish Ghoshal; Jean Honorio (CoRR, 2019)

Minimax Bounds for Structured Prediction Based on Factor Graphs. - Kevin Bello; Asish Ghoshal; Jean Honorio (AISTATS, 2020)

Fairness constraints can help exact inference in structured prediction. - Kevin Bello; Jean Honorio (NeurIPS, 2020)

Fundamental Limits of Adversarial Learning. - Kevin Bello; Qiuling Xu; Jean Honorio (CoRR, 2020)

A Le Cam Type Bound for Adversarial Learning and Applications. - Qiuling Xu; Kevin Bello; Jean Honorio (ISIT, 2021)

Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees. - Gregory Dexter; Kevin Bello; Jean Honorio (NeurIPS, 2021)

Inverse Reinforcement Learning in the Continuous Setting with Formal Guarantees. - Gregory Dexter; Kevin Bello; Jean Honorio (CoRR, 2021)

A Thorough View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy. - Kevin Bello; Chuyang Ke; Jean Honorio (CoRR, 2021)

A View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy. - Kevin Bello; Chuyang Ke; Jean Honorio (AISTATS, 2022)

On the Fundamental Limits of Exact Inference in Structured Prediction. - Hanbyul Lee 001; Kevin Bello; Jean Honorio (ISIT, 2022)

DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization. - Kevin Bello; Bryon Aragam; Pradeep Ravikumar (NeurIPS, 2022)

Optimizing NOTEARS Objectives via Topological Swaps. - Chang Deng; Kevin Bello; Bryon Aragam; Pradeep Kumar Ravikumar (ICML, 2023)

iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models. - Tianyu Chen; Kevin Bello; Bryon Aragam; Pradeep Ravikumar (NeurIPS, 2023)

Global Optimality in Bivariate Gradient-based DAG Learning. - Chang Deng; Kevin Bello; Pradeep Ravikumar; Bryon Aragam (NeurIPS, 2023)

Bayesian Dynamic DAG Learning: Application in Discovering Dynamic Effective Connectome of Brain. - Abdolmahdi Bagheri; Mohammad Pasande; Kevin Bello; Alireza Akhondi Asl; Babak Nadjar Araabi (CoRR, 2023)

Identifying General Mechanism Shifts in Linear Causal Representations. - Tianyu Chen; Kevin Bello; Francesco Locatello; Bryon Aragam; Pradeep Ravikumar (NeurIPS, 2024)

Markov Equivalence and Consistency in Differentiable Structure Learning. - Chang Deng; Kevin Bello; Pradeep Ravikumar; Bryon Aragam (NeurIPS, 2024)

Identifying Causal Changes Between Linear Structural Equation Models. - Vineet Malik; Kevin Bello; Asish Ghoshal; Jean Honorio (UAI, 2024)

C2P: Featuring Large Language Models with Causal Reasoning. - Abdolmahdi Bagheri; Matin Alinejad; Kevin Bello; Alireza Akhondi Asl (CoRR, 2024)

Likelihood-based Differentiable Structure Learning. - Chang Deng; Kevin Bello; Pradeep Ravikumar; Bryon Aragam (CoRR, 2024)

Discovering the effective connectome of the brain with dynamic Bayesian DAG learning. - Abdolmahdi Bagheri; Mohammad Pasande; Kevin Bello; Babak Nadjar Araabi; Alireza Akhondi Asl (NeuroImage, 2024)

Towards Fair Graph Learning without Demographic Information. - Zichong Wang; Nhat Hoang; Xingyu Zhang; Kevin Bello; Xiangliang Zhang 001; Sundararaja Sitharama Iyengar; Wenbin Zhang 002 (AISTATS, 2025)