Matej Zecevic

According to our database, Matej Zecevic authored at least 21 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Structural causal models reveal confounder bias in linear program modelling.

Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

Mach. Learn., 2024

2023

Causal Parrots: Large Language Models May Talk Causality But Are Not Causal.

Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting

CoRR, 2023

Do Not Marginalize Mechanisms, Rather Consolidate!

Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Continual Causal Abstractions.

Matej Zecevic, Moritz Willig, Florian Peter Busch, Jonas Seng

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

Causal Concept Identification in Open World Environments.

Moritz Willig, Matej Zecevic, Jonas Seng, Florian Peter Busch

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

Treatment Effect Estimation to Guide Model Optimization in Continual Learning.

Jonas Seng, Florian Peter Busch, Matej Zecevic, Moritz Willig

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

Continually Updating Neural Causal Models.

Florian Peter Busch, Jonas Seng, Moritz Willig, Matej Zecevic

Proceedings of the AAAI Bridge Program on Continual Causality, 2023

2022

Pearl Causal Hierarchy on Image Data: Intricacies & Challenges.

Matej Zecevic, Moritz Willig, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

On How AI Needs to Change to Advance the Science of Drug Discovery.

Kieran Didi, Matej Zecevic

CoRR, 2022

Can Foundation Models Talk Causality?

Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Attributions Beyond Neural Networks: The Linear Program Case.

Florian Peter Busch, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami

CoRR, 2022

Towards a Solution to Bongard Problems: A Causal Approach.

Salahedine Youssef, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation.

Jonas Seng, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Machines Explaining Linear Programs.

David Steinmann, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

Finding Structure and Causality in Linear Programs.

Matej Zecevic, Florian Peter Busch, Devendra Singh Dhami, Kristian Kersting

CoRR, 2022

2021

The Causal Loss: Driving Correlation to Imply Causation.

Moritz Willig, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2021

On the Tractability of Neural Causal Inference.

Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2021

Structural Causal Interpretation Theorem.

Matej Zecevic, Devendra Singh Dhami, Constantin A. Rothkopf, Kristian Kersting

CoRR, 2021

Relating Graph Neural Networks to Structural Causal Models.

Matej Zecevic, Devendra Singh Dhami, Petar Velickovic, Kristian Kersting

CoRR, 2021

Intriguing Parameters of Structural Causal Models.

Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, 2021

Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models.

Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021