| Relating graph neural networks to structural causal models M Zečević, DS Dhami, P Veličković, K Kersting arXiv preprint arXiv:2109.04173, 2021 | 42 | 2021 |
| 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 | 31 | 2021 |
| 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 | 25 | 2023 |
| Can foundation models talk causality? M Willig, M Zečević, DS Dhami, K Kersting arXiv preprint arXiv:2206.10591, 2022 | 14 | 2022 |
| Causal parrots: Large language models may talk causality but are not causal M Willig, M Zecevic, DS Dhami, K Kersting preprint 8, 2023 | 5 | 2023 |
| Probing for correlations of causal facts: Large language models and causality M Willig, M Zečević, DS Dhami, K Kersting | 5 | 2022 |
| Towards a solution to bongard problems: A causal approach S Youssef, M Zečević, DS Dhami, K Kersting arXiv preprint arXiv:2206.07196, 2022 | 3 | 2022 |
| Tearing Apart NOTEARS: Controlling the Graph Prediction via Variance Manipulation J Seng, M Zečević, DS Dhami, K Kersting arXiv preprint arXiv:2206.07195, 2022 | 2 | 2022 |
| On How AI Needs to Change to Advance the Science of Drug Discovery K Didi, M Zečević arXiv preprint arXiv:2212.12560, 2022 | 1 | 2022 |
| The Causal Loss: Driving Correlation to Imply Causation M Willig, M Zečević, DS Dhami, K Kersting arXiv preprint arXiv:2110.12066, 2021 | 1 | 2021 |
| 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 | 1 | 2021 |
| 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 |
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLISGeverifieerd e-mailadres voor cs.tu-darmstadt.de
