Discovering the effective connectome of the brain with dynamic Bayesian DAG learning.
NeuroImage, 2024
Likelihood-based Differentiable Structure Learning.
CoRR, 2024
C2P: Featuring Large Language Models with Causal Reasoning.
CoRR, 2024
Identifying Causal Changes Between Linear Structural Equation Models.
Proceedings of the Uncertainty in Artificial Intelligence, 2024
Markov Equivalence and Consistency in Differentiable Structure Learning.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Identifying General Mechanism Shifts in Linear Causal Representations.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Bayesian Dynamic DAG Learning: Application in Discovering Dynamic Effective Connectome of Brain.
CoRR, 2023
Global Optimality in Bivariate Gradient-based DAG Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Optimizing NOTEARS Objectives via Topological Swaps.
Proceedings of the International Conference on Machine Learning, 2023
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
On the Fundamental Limits of Exact Inference in Structured Prediction.
Proceedings of the IEEE International Symposium on Information Theory, 2022
A View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
A Thorough View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy.
CoRR, 2021
Inverse Reinforcement Learning in the Continuous Setting with Formal Guarantees.
CoRR, 2021
Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
A Le Cam Type Bound for Adversarial Learning and Applications.
Proceedings of the IEEE International Symposium on Information Theory, 2021
Fundamental Limits of Adversarial Learning.
CoRR, 2020
Fairness constraints can help exact inference in structured prediction.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Minimax Bounds for Structured Prediction Based on Factor Graphs.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Minimax bounds for structured prediction.
CoRR, 2019
Exact inference in structured prediction.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Improving Topic Coherence Using Entity Extraction Denoising.
Prague Bull. Math. Linguistics, 2018
Computationally and statistically efficient learning of causal Bayes nets using path queries.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Learning latent variable structured prediction models with Gaussian perturbations.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Learning Bayes networks using interventional path queries in polynomial time and sample complexity.
CoRR, 2017