Ordering-based Causal Discovery from Generalized Score Matching
Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2026.
Research
Causal Discovery in the Wild: A Voting-Theoretic Ensemble Approach
Proceedings of the 14th International Conference on Learning Representations, 2026.
Preserving Clusters in Prompt Learning for Unsupervised Domain Adaptation
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025.
ACCESS: A Benchmark for Abstract Causal Event Discovery and Reasoning
Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics, 2025.
Optimal Transport for Structure Learning Under Missing Data
Proceedings of the 41st International Conference on Machine Learning, 2024.
Parameter Estimation in DAGs from Incomplete Data via Optimal Transport.
Proceedings of the 41st International Conference on Machine Learning, 2024.
Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023.
Best Student Research Paper Award
An Additive Instance-Wise Approach to Multi-class Model Interpretation
Proceedings of the 11th International Conference on Learning Representations, 2023.
Introduction to Causal Thinking
If correlation is not causation, then what is?
How Machines Are Taught
Leaving those mathematical fuzz aside, I am urged to take one step away from the mainstream and rethink how machines learn.
Assumptions of Linear Models
I explain the assumptions underlying Linear Regression, an old-school machine learning model but widely used today.