Matej Zečević
Causal Explanations of Structural Causal Models
📺 Causal Inference Interest Group
Matej Zečević, Devendra Singh Dhami, Christina Winkler, Thomas Kipf, Robert Peharz, Petar Veličković
NeurIPS 2022 Workshop on neuro Causal and Symbolic AI (nCSI)
🎫 NeurIPS 2022
Matej Zečević, Moritz Willig, Jonas Seng, Florian Peter Busch
Continual Causal Abstractions
📰 AAAI 2023 Bridge Continual Causality
Kieran Didi, Matej Zečević
On How AI Needs to Change to Advance the Science of Drug Discovery
📰 arXiv (2212.12560)
Moritz Willig*, Matej Zečević*, Devendra Singh Dhami, Kristian Kersting
Can Foundation Models Talk Causality?
📰 UAI 2022 Workshop on Causal Representation Learning (CRL)
Matej Zečević
Hands-on: Causality for Machine Learning (Coding Live Tutorial)
📺 Int’l Summer School on Data Science
Matej Zečević
Causality for Machine Learning II
📺 Int’l Summer School on Data Science
Matej Zečević
Causality for Machine Learning I
📺 Int’l Summer School on Data Science
David Steinmann, Matej Zečević, Devendra Singh Dhami, Kristian Kersting
Machines Explaining Linear Programs
📰 arXiv (2206.07194)
Salahedine Youssef, Matej Zečević, Devendra Singh Dhami, Kristian Kersting
Towards a Solution to Bongard Problems: A Causal Approach
📰 arXiv (2206.07196)
Florian Peter Busch, Matej Zečević, Devendra Singh Dhami, Kristian Kersting
Attributions Beyond Neural Networks: The Linear Program Case
📰 arXiv (2206.07203)
Jonas Seng, Matej Zečević, Devendra Singh Dhami, Kristian Kersting
Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation
📰 arXiv (2206.07195)
Matej Zečević
Towards Deep Understanding: An Introductory Tutorial on Causal Inference (Coding Live Tutorial)
📺 Serbian Machine Learning Workshop (Part of Eastern European Machine Learning Summer School)
Matej Zečević, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting
Finding Structure and Causality in Linear Programs
📰 ICLR 2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality (OSC)
