| Making deep neural networks right for the right scientific reasons by interacting with their explanations P Schramowski, W Stammer, S Teso, A Brugger, F Herbert, X Shao, ... Nature Machine Intelligence 2 (8), 476-486, 2020 | 243 | 2020 |
| Random sum-product networks: A simple and effective approach to probabilistic deep learning R Peharz, A Vergari, K Stelzner, A Molina, X Shao, M Trapp, K Kersting, ... Uncertainty in Artificial Intelligence, 334-344, 2020 | 130 | 2020 |
| Conditional sum-product networks: Imposing structure on deep probabilistic architectures X Shao, A Molina, A Vergari, K Stelzner, R Peharz, T Liebig, K Kersting International Conference on Probabilistic Graphical Models, 401-412, 2020 | 47 | 2020 |
| Right for better reasons: Training differentiable models by constraining their influence functions X Shao, A Skryagin, W Stammer, P Schramowski, K Kersting Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9533-9540, 2021 | 35 | 2021 |
| Neural-symbolic argumentation mining: An argument in favor of deep learning and reasoning A Galassi, K Kersting, M Lippi, X Shao, P Torroni Frontiers in big Data 2, 52, 2020 | 20 | 2020 |
| Right for the wrong scientific reasons: Revising deep networks by interacting with their explanations P Schramowski, W Stammer, S Teso, A Brugger, HG Luigs, AK Mahlein, ... arXiv preprint arXiv:2001.05371, 2020 | 20 | 2020 |
| Conditional sum-product networks: Modular probabilistic circuits via gate functions X Shao, A Molina, A Vergari, K Stelzner, R Peharz, T Liebig, K Kersting International Journal of Approximate Reasoning 140, 298-313, 2022 | 17 | 2022 |
| Towards understanding and arguing with classifiers: Recent progress X Shao, T Rienstra, M Thimm, K Kersting Datenbank-Spektrum 20 (2), 171-180, 2020 | 9 | 2020 |
| Making deep neural networks right for the right scientific reasons by interacting with their explanations. Nat Mach Intell 2: 476–486 P Schramowski, W Stammer, S Teso, A Brugger, F Herbert, X Shao, ... | 6 | 2020 |
| Right for the right latent factors: debiasing generative models via disentanglement X Shao, K Stelzner, K Kersting arXiv preprint arXiv:2202.00391, 2022 | 5 | 2022 |
| Independence and D-separation in Abstract Argumentation. T Rienstra, M Thimm, K Kersting, X Shao KR, 713-722, 2020 | 5 | 2020 |
| Gradient-based Counterfactual Explanations using Tractable Probabilistic Models X Shao, K Kersting arXiv preprint arXiv:2205.07774, 2022 | 2 | 2022 |
| Modelling Multivariate Ranking Functions with Min-Sum Networks X Shao, Z Yu, A Skryagin, T Rienstra, M Thimm, K Kersting Scalable Uncertainty Management: 14th International Conference, SUM 2020 …, 2020 | 1 | 2020 |
| Explaining and Interactively Debugging Deep Models X Shao Technische Universität Darmstadt, 2022 | | 2022 |
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CAIRNE & ELLISVerified email at cs.tu-darmstadt.de
