| 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, 30416-30428, 2023 | 15 | 2023 |
| 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 | 14 | 2023 |
| Neurosymbolic markov models L De Smet, G Venturato, L De Raedt, G Marra ICML 2024 Workshop on Structured Probabilistic Inference {\&} Generative …, 2024 | 2 | 2024 |
| Relational neurosymbolic Markov models L De Smet, G Venturato, L De Raedt, G Marra arXiv preprint arXiv:2412.13023, 2024 | 1 | 2024 |
| A Fast Convoluted Story: Scaling Probabilistic Inference for Integer Arithmetic L De Smet, PZD Martires arXiv preprint arXiv:2410.12389, 2024 | | 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 |
| Inferring Missing CV Skills using PU Learning and Variational Inference P Delobelle International workshop on AI for Human Resources and Public Employment …, 2023 | | 2023 |
| 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 Reinforcement Learning With Sequential Guarantees L De Smet, G Venturato, G Marra, L De Raedt | | |
| Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick: Supplementary Material L De Smet, E Sansone, PZ Dos Martires | | |
| 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 Universityایمیل تأیید شده در oru.se