Matej Zecevic

According to our database, Matej Zecevic authored at least 29 papers between 2021 and 2025.

Collaborative distances:

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

2025

Causal Explanations Over Time: Articulated Reasoning for Interactive Environments.

Sebastian Rödling, Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

CoRR, June, 2025

Elucidating linear programs by neural encodings.

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

Frontiers Artif. Intell., 2025

STRICTA: Structured Reasoning in Critical Text Assessment for Peer Review and Beyond.

Nils Dycke, Matej Zecevic, Ilia Kuznetsov, Beatrix Suess, Kristian Kersting, Iryna Gurevych

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Structural causal models reveal confounder bias in linear program modelling.

Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

Mach. Learn., 2024

Diagnostic Reasoning in Natural Language: Computational Model and Application.

Nils Dycke, Matej Zecevic, Ilia Kuznetsov, Beatrix Suess, Kristian Kersting, Iryna Gurevych

CoRR, 2024

χSPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains.

Harsh Poonia, Moritz Willig, Zhongjie Yu, Matej Zecevic, Kristian Kersting, Devendra Singh Dhami

Proceedings of the Uncertainty in Artificial Intelligence, 2024

"Do Not Disturb My Circles!" Identifying the Type of Counterfactual at Hand (Short Paper).

Moritz Willig, Matej Zecevic, Kristian Kersting

Proceedings of the Robust Argumentation Machines - First International Conference, 2024

Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG.

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

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

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

Trans. Mach. Learn. Res., 2023

Not All Causal Inference is the Same.

Matej Zecevic, Devendra Singh Dhami, Kristian Kersting

Trans. Mach. Learn. Res., 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