ReSeg: A Recurrent Neural Network for Object Segmentation. - Francesco Visin; Kyle Kastner; Aaron C. Courville; Yoshua Bengio; Matteo Matteucci; KyungHyun Cho (CoRR, 2015)

ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks. - Francesco Visin; Kyle Kastner; Kyunghyun Cho; Matteo Matteucci; Aaron C. Courville; Yoshua Bengio (CoRR, 2015)

ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation. - Francesco Visin; Adriana Romero; Kyunghyun Cho; Matteo Matteucci; Marco Ciccone; Kyle Kastner; Yoshua Bengio; Aaron C. Courville (CVPR Workshops, 2016)

Theano: A Python framework for fast computation of mathematical expressions. - Rami Al-Rfou; Guillaume Alain; Amjad Almahairi; Christof Angermüller; Dzmitry Bahdanau; Nicolas Ballas; Frédéric Bastien; Justin Bayer; Anatoly Belikov; Alexander Belopolsky; Yoshua Bengio; Arnaud Bergeron; et al. (CoRR, 2016)

A guide to convolution arithmetic for deep learning. - Vincent Dumoulin; Francesco Visin (CoRR, 2016)

Multi-view Stereo with Single-View Semantic Mesh Refinement. - Andrea Romanoni; Marco Ciccone; Francesco Visin; Matteo Matteucci (ICCV Workshops, 2017)

Mollifying Networks. - Çaglar Gülçehre; Marcin Moczulski; Francesco Visin; Yoshua Bengio (ICLR (Poster), 2017)

PixelVAE: A Latent Variable Model for Natural Images. - Ishaan Gulrajani; Kundan Kumar; Faruk Ahmed; Adrien Ali Taïga; Francesco Visin; David Vázquez 001; Aaron C. Courville (ICLR (Poster), 2017)

Deep recurrent neural networks for visual scene understanding. - Francesco Visin (2017)

ReConvNet: Video Object Segmentation with Spatio-Temporal Features Modulation. - Francesco Lattari; Marco Ciccone; Matteo Matteucci; Jonathan Masci; Francesco Visin (CoRR, 2018)

Continual Unsupervised Representation Learning. - Dushyant Rao; Francesco Visin; Andrei A. Rusu; Razvan Pascanu; Yee Whye Teh; Raia Hadsell (NeurIPS, 2019)

Learning rich touch representations through cross-modal self-supervision. - Martina Zambelli; Yusuf Aytar; Francesco Visin; Yuxiang Zhou; Raia Hadsell (CoRL, 2020)

Meta-Learning with Warped Gradient Descent. - Sebastian Flennerhag; Andrei A. Rusu; Razvan Pascanu; Francesco Visin; Hujun Yin; Raia Hadsell (ICLR, 2020)

Small Data, Big Decisions: Model Selection in the Small-Data Regime. - Jörg Bornschein; Francesco Visin; Simon Osindero (ICML, 2020)

Temporal Difference Uncertainties as a Signal for Exploration. - Sebastian Flennerhag; Jane X. Wang; Pablo Sprechmann; Francesco Visin; Alexandre Galashov; Steven Kapturowski; Diana L. Borsa; Nicolas Heess; André Barreto 001; Razvan Pascanu (CoRR, 2020)

Gemma 2: Improving Open Language Models at a Practical Size. - Morgane Rivière; Shreya Pathak; Pier Giuseppe Sessa; Cassidy Hardin; Surya Bhupatiraju; Léonard Hussenot; Thomas Mesnard; Bobak Shahriari; Alexandre Ramé; Johan Ferret; Peter Liu; Pouya Tafti; et al. (CoRR, 2024)

Utility-inspired Reward Transformations Improve Reinforcement Learning Training of Language Models. - Roberto-Rafael Maura-Rivero; Chirag Nagpal; Roma Patel; Francesco Visin (CoRR, 2025)

Jackpot! Alignment as a Maximal Lottery. - Roberto-Rafael Maura-Rivero; Marc Lanctot; Francesco Visin; Kate Larson (CoRR, 2025)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)