Event Clustering and Classification from Social Media: Watershed-based and Kernel Methods. - Truc-Vien Nguyen; Minh-Son Dao; Riccardo Mattivi; Emanuele Sansone; Francesco G. B. De Natale; Giulia Boato (MediaEval, 2013)

Synchronizing Multi-User Photo Galleries with MRF. - Emanuele Sansone; Giulia Boato; Minh-Son Dao (MediaEval, 2014)

Classtering: Joint Classification and Clustering with Mixture of Factor Analysers. - Emanuele Sansone; Andrea Passerini; Francesco G. B. De Natale (ECAI, 2016)

Efficient Training for Positive Unlabeled Learning. - Emanuele Sansone (CoRR, 2016)

Training Feedforward Neural Networks with Standard Logistic Activations is Feasible. - Emanuele Sansone; Francesco G. B. De Natale (CoRR, 2017)

Automatic Synchronization of Multi-user Photo Galleries. - Emanuele Sansone; Konstantinos Apostolidis; Nicola Conci; Giulia Boato; Vasileios Mezaris; Francesco G. B. De Natale (IEEE Trans. Multim., 2017)

Plummer Autoencoders. - Emanuele Sansone; Quoc-Tin Phan; Francesco G. B. De Natale (CoRR, 2018)

Towards Uncovering the True Use of Unlabeled Data in Machine Learning. - Emanuele Sansone (2018)

Efficient Training for Positive Unlabeled Learning. - Emanuele Sansone; Francesco G. B. De Natale; Zhi-Hua Zhou (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

Coulomb Autoencoders. - Emanuele Sansone; Hafiz Tiomoko Ali; Jiacheng Sun (ECAI, 2020)

Leveraging Hidden Structure in Self-Supervised Learning. - Emanuele Sansone (CoRR, 2021)

LSB: Local Self-Balancing MCMC in Discrete Spaces. - Emanuele Sansone (ICML, 2022)

VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming. - Eleonora Misino; Giuseppe Marra; Emanuele Sansone (NeurIPS, 2022)

GEDI: GEnerative and DIscriminative Training for Self-Supervised Learning. - Emanuele Sansone; Robin Manhaeve (CoRR, 2022)

Differentiable Sampling of Categorical Distributions Using the CatLog-Derivative Trick. - Lennert De Smet; Emanuele Sansone; Pedro Zuidberg Dos Martires (NeurIPS, 2023)

Learning Symbolic Representations Through Joint GEnerative and DIscriminative Training. - Emanuele Sansone; Robin Manhaeve (CoRR, 2023)

The Triad of Failure Modes and a Possible Way Out. - Emanuele Sansone (CoRR, 2023)

EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic. - Victor Verreet; Lennert De Smet; Luc De Raedt; Emanuele Sansone (ECAI, 2024)

A Bayesian Unification of Self-Supervised Clustering and Energy-Based Models. - Emanuele Sansone; Robin Manhaeve (CoRR, 2024)

(Deep) Generative Geodesics. - Beomsu Kim; Michael Puthawala; Jong Chul Ye; Emanuele Sansone (CoRR, 2024)

Failure-Proof Non-Contrastive Self-Supervised Learning. - Emanuele Sansone; Tim Lebailly; Tinne Tuytelaars (CoRR, 2024)