Emanuele Sansone bio photo

Emanuele Sansone

PhD in machine learning and artificial intelligence.

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Representative 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
  • V. Verreet, L. De Smet, E. Sansone EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic. European Conference on Artificial Intelligence (ECAI), 2024.   PDF
  • B. Kim, M. Puthawala, J.C. Ye, E. Sansone (Deep) Generative Geodesics. ICML GRaM Workshop, 2024.   PDF

2023

  • 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
  • E. Sansone, R. Manhaeve Learning Symbolic Representations Through Joint GEnerative and DIscriminative Training. ICLR NeSy-GeMs Workshop, 2023.   PDF Talk

2022

  • 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

2020

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

2018

  • 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

2016

  • 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