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Matej Zečević
Matej Zečević
PhD Candidate @ TU Darmstadt
Verified email at tu-darmstadt.de - Homepage
Title
Cited by
Cited by
Year
Relating graph neural networks to structural causal models
M Zečević, DS Dhami, P Veličković, K Kersting
arXiv preprint arXiv:2109.04173, 2021
422021
Interventional sum-product networks: Causal inference with tractable probabilistic models
M Zečević, D Dhami, A Karanam, S Natarajan, K Kersting
Advances in neural information processing systems 34, 15019-15031, 2021
312021
Causal parrots: Large language models may talk causality but are not causal
M Zečević, M Willig, DS Dhami, K Kersting
arXiv preprint arXiv:2308.13067, 2023
252023
Can foundation models talk causality?
M Willig, M Zečević, DS Dhami, K Kersting
arXiv preprint arXiv:2206.10591, 2022
142022
Causal parrots: Large language models may talk causality but are not causal
M Willig, M Zecevic, DS Dhami, K Kersting
preprint 8, 2023
62023
Probing for correlations of causal facts: Large language models and causality
M Willig, M Zečević, DS Dhami, K Kersting
52022
Towards a solution to bongard problems: A causal approach
S Youssef, M Zečević, DS Dhami, K Kersting
arXiv preprint arXiv:2206.07196, 2022
32022
Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation
J Seng, M Zečević, DS Dhami, K Kersting
arXiv preprint arXiv:2206.07195, 2022
22022
On How AI Needs to Change to Advance the Science of Drug Discovery
K Didi, M Zečević
arXiv preprint arXiv:2212.12560, 2022
12022
The Causal Loss: Driving Correlation to Imply Causation
M Willig, M Zečević, DS Dhami, K Kersting
arXiv preprint arXiv:2110.12066, 2021
12021
A Taxonomy for Inference in Causal Model Families
M Zečević, DS Dhami, K Kersting
arXiv preprint arXiv:2110.12052, 2021
1*2021
Causal explanations of structural causal models
M Zečević, DS Dhami, CA Rothkopf, K Kersting
arXiv preprint arXiv:2110.02395, 2021
12021
Can Linear Programs Have Adversarial Examples? A Causal Perspective
M Zečević, D Singh Dhami, K Kersting
arXiv e-prints, arXiv: 2105.12697, 2021
1*2021
Do Not Marginalize Mechanisms, Rather Consolidate!
M Willig, M Zečević, D Dhami, K Kersting
Advances in Neural Information Processing Systems 36, 2024
2024
Structural causal models reveal confounder bias in linear program modelling
M Zečević, DS Dhami, K Kersting
Machine Learning, 1-21, 2024
2024
Elucidating Linear Programs by Neural Encodings
FP Busch, M Zečević, K Kersting, DS Dhami
Authorea Preprints, 2023
2023
Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG
J Seng, M Zečević, DS Dhami, K Kersting
The Twelfth International Conference on Learning Representations, 2023
2023
Causal Concept Identification in Open World Environments
M Willig, M Zečević, J Seng, FP Busch
AAAI Bridge Program on Continual Causality, 52-58, 2023
2023
Treatment Effect Estimation to Guide Model Optimization in Continual Learning
J Seng, FP Busch, M Zečević, M Willig
AAAI Bridge Program on Continual Causality, 38-44, 2023
2023
Continually Updating Neural Causal Models
FP Busch, J Seng, M Willig, M Zečević
AAAI Bridge Program on Continual Causality, 30-37, 2023
2023
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