| Efficient Training for Positive Unlabeled Learning E Sansone, F De Natale, ZH Zhou IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 2018 | 76 | 2018 |
| Event Clustering and Classification from Social Media: Watershed-based and Kernel Methods. TV Nguyen, MS Dao, R Mattivi, E Sansone, FGB De Natale, G Boato MediaEval Workshop, 2013 | 29 | 2013 |
| VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming E Misino, G Marra, E Sansone Neural Information Processing Systems (NeurIPS), 2022 | 13 | 2022 |
| Classtering: Joint classification and clustering with mixture of factor analysers E Sansone, A Passerini, FGB De Natale European Conference on Artificial Intelligence (ECAI), 2016 | 10 | 2016 |
| Automatic synchronization of multi-user photo galleries E Sansone, K Apostolidis, N Conci, G Boato, V Mezaris, FGB De Natale IEEE Transactions on Multimedia (TMM), 2017 | 6 | 2017 |
| LSB: Local Self-Balancing MCMC in Discrete Spaces E Sansone International Conference on Machine Learning (ICML), 2022 | 5 | 2022 |
| Synchronizing Multi-User Photo Galleries with MRF. E Sansone, G Boato, MS Dao MediaEval, 2014 | 5 | 2014 |
| Learning Symbolic Representations Through Joint GEnerative and DIscriminative Training E Sansone, R Manhaeve International Conference on Learning Representations Workshop (ICLR NeSy-GeMs), 2023 | 3 | 2023 |
| GEDI: GEnerative and DIscriminative Training for Self-Supervised Learning E Sansone, R Manhaeve https://arxiv.org/abs/2212.13425, 2022 | 3 | 2022 |
| Training Feedforward Neural Networks with Standard Logistic Activations is Feasible E Sansone, FGB De Natale arXiv preprint arXiv:1710.01013, 2017 | 3 | 2017 |
| The Triad of Failure Modes and a Possible Way Out E Sansone Neural Information Processing Systems Workshop (NeurIPS SSLTheoryPractice), 2023 | 1 | 2023 |
| Coulomb Autoencoders E Sansone, HT Ali, J Sun European Conference on Artificial Intelligence (ECAI), 2020 | 1 | 2020 |
| A Bayesian Unification of Self-Supervised Clustering and Energy-Based Models E Sansone, R Manhaeve https://arxiv.org/abs/2401.00873, 2024 | | 2024 |
| Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick L De Smet, E Sansone, P Zuidberg Dos Martires Neural Information Processing Systems (NeurIPS), 2023 | | 2023 |
| Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick L De Smet, E Sansone, P Zuidberg Dos Martires International Conference on Machine Learning Workshop (ICML DiffAE), 2023 | | 2023 |
| VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming E Misino, G Marra, E Sansone International Conference on Machine Learning Workshop (ICML KLR), 2023 | | 2023 |
| EXPLAIN, AGREE and LEARN: A Recipe for Scalable Neural-Symbolic Learning V Verreet, L De Smet, E Sansone International Conference on Machine Learning Workshop (ICML KLR), 2023 | | 2023 |
| Learning Symbolic Representations Through Joint GEnerative and DIscriminative Training (Extended Abstract) E Sansone, R Manhaeve International Joint Conferences on Artificial Intelligence Workshop (IJCAI KBCG), 2023 | | 2023 |
| Towards Uncovering the True Use of Unlabeled Data in Machine Learning E Sansone University of Trento (PhD Thesis), 2018 | | 2018 |
