Papers & Talks
2022
Can Foundation Models Talk Causality?
Machines Explaining Linear Programs
Towards a Solution to Bongard Problems: A Causal Approach
Attributions Beyond Neural Networks: The Linear Program Case
Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation
Towards Deep Understanding: An Introductory Tutorial on Causal Inference (Coding Live Tutorial)
Finding Structure and Causality in Linear Programs
📰 ICLR 2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality (OSC)
2021
Towards Neuro-Causality: Relating Graph Neural Networks to Structural Causal Models (Extended Version + Active Session Discussions)
The Causal Loss: Driving Correlation to Imply Causation
On the Tractability of Neural Causal Inference
Structural Causal Interpretation Theorem
Towards Neuro-Causality: Relating Graph Neural Networks to Structural Causal Models
Relating Graph Neural Networks to Structural Causal Models
Intriguing Parameters of Structural Causal Models
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models
📺 NeurIPS 2021
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models
📰 NeurIPS 2021