Selected List of Publications

The list of all publications is available in the CV.

2024

E. Sansone, R. Manhaeve A Bayesian Unification of Self-Supervised Clustering and Energy-Based Models. arXiv, 2024. PDF

L. De Smet, E. Sansone, P. Z. D. Martires Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick. Neural Information Processing Systems (NeurIPS), 2023. PDF
V. Verreet, L. De Smet, E. Sansone EXPLAIN, AGREE and LEARN: A Recipe for Scalable Neural-Symbolic Learning. ICML KLR Workshop, 2023. PDF
E. Sansone, R. Manhaeve Learning Symbolic Representations Through Joint GEnerative and DIscriminative Training. ICLR NeSy-GeMs Workshop, 2023. PDF Talk

E. Sansone, R. Manhaeve GEDI: GEnerative and DIscriminative Training for Self-Supervised Learning. arXiv, 2022. PDF Talk
E. Sansone LSB: Local Self-Balancing MCMC in Discrete Spaces. International Conference on Machine Learning (ICML), 2022. Blog PDF Code Talk
E. Misino, G. Marra, E. Sansone VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming. Neural Information Processing Systems (NeurIPS), 2022. PDF Code Talk

E. Sansone, H. T. Ali, S. Jiacheng Coulomb Autoencoders. European Conference on Artificial Intelligence (ECAI), 2020. PDF Code Slides Talk

E. Sansone Towards Uncovering the True Use of Unlabeled Data in Machine Learning. PhD thesis. PDF
E. Sansone, F.G.B. De Natale, Zhi-Hua Zhou. Efficient Training for Positive Unlabeled Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). PDF Code

E. Sansone, A. Passerini, F.G.B. De Natale. Classtering: Joint Classification and Clustering with Mixture of Factor Analysers. European Conference on Artificial Intelligence (ECAI), 2016. PDF Code Slides