| Neural probabilistic logic programming in discrete-continuous domains L De Smet, PZ Dos Martires, R Manhaeve, G Marra, A Kimmig, ... Uncertainty in Artificial Intelligence, 529-538, 2023 | 7 | 2023 |
| Differentiable sampling of categorical distributions using the catlog-derivative trick L De Smet, E Sansone, P Zuidberg Dos Martires Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |
| EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic V Verreet, L De Smet, L De Raedt, E Sansone arXiv preprint arXiv:2408.08133, 2024 | | 2024 |
| EXPLAIN, AGREE and LEARN: A Recipe for Scalable Neural-Symbolic Learning V Verreet, L De Smet, E Sansone ICML Workshop: Knowledge and Logical Reasoning in the Era of Data-driven …, 2023 | | 2023 |
| Neurosymbolic Markov Models L De Smet, G Venturato, L De Raedt, G Marra ICML 2024 Workshop on Structured Probabilistic Inference {\&} Generative …, 0 | | |
| Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick: Supplementary Material L De Smet, E Sansone, PZ Dos Martires | | |
| Inferring Missing CV Skills using PU Learning and Variational Inference V Verreet, L De Smet, R Manhaeve, P Delobelle, J Bekker | | |
| Tensorised Probabilistic Inference for Neural Probabilistic Logic Programming L De Smet, R Manhaeve, G Marra, PZ Dos Martires The 5th Workshop on Tractable Probabilistic Modeling, 0 | | |
Pedro Zuidberg Dos MartiresÖrebro University在 oru.se 的电子邮件经过验证
