Yann Ollivier - RankMe

58 papers A* 11A 1Journal 39Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Likelihood-Based Reward Designs for General LLM Reasoning. CoRR Ariel Kwiatkowski, Natasha Butt, Ismail Labiad, Julia Kempe, Yann Ollivier
2026	J	`jnl`	Teaching Models to Teach Themselves: Reasoning at the Edge of Learnability. CoRR Shobhita Sundaram, John Quan, Ariel Kwiatkowski, Kartik Ahuja, Yann Ollivier, Julia Kempe
2025	J	`jnl`	Soft Tokens, Hard Truths. CoRR Natasha Butt, Ariel Kwiatkowski, Ismail Labiad, Julia Kempe, Yann Ollivier
2025	J	`jnl`	Tackling the Zero-Shot Reinforcement Learning Loss Directly. CoRR Yann Ollivier
2025	J	`jnl`	Which Features are Best for Successor Features? CoRR Yann Ollivier
2024	A*	`conf`	Fast Imitation via Behavior Foundation Models. ICLR Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati, Alessandro Lazaric, Yann Ollivier
2024	J	`jnl`	Finer Behavioral Foundation Models via Auto-Regressive Features and Advantage Weighting. CoRR Edoardo Cetin, Ahmed Touati, Yann Ollivier
2024	A*	`conf`	Simple Ingredients for Offline Reinforcement Learning. ICML Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati
2024	J	`jnl`	Simple Ingredients for Offline Reinforcement Learning. CoRR Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta, Alessandro Lazaric, Yann Ollivier, Ahmed Touati
2023	A*	`conf`	Does Zero-Shot Reinforcement Learning Exist? ICLR Ahmed Touati, Jérémy Rapin, Yann Ollivier
2022	J	`jnl`	Agnostic Physics-Driven Deep Learning. CoRR Benjamin Scellier, Siddhartha Mishra, Yoshua Bengio, Yann Ollivier
2022	J	`jnl`	Does Zero-Shot Reinforcement Learning Exist? CoRR Ahmed Touati, Jérémy Rapin, Yann Ollivier
2021	A*	`conf`	Learning One Representation to Optimize All Rewards. NeurIPS Ahmed Touati, Yann Ollivier
2021	J	`jnl`	Learning One Representation to Optimize All Rewards. CoRR Ahmed Touati, Yann Ollivier
2021	J	`jnl`	Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint. CoRR Léonard Blier, Corentin Tallec, Yann Ollivier
2021	J	`jnl`	Unbiased Methods for Multi-Goal Reinforcement Learning. CoRR Léonard Blier, Yann Ollivier
2020	J	`jnl`	Interpreting a Penalty as the Influence of a Bayesian Prior. CoRR Pierre Wolinski, Guillaume Charpiat, Yann Ollivier
2019	A*	`conf`	First-Order Adversarial Vulnerability of Neural Networks and Input Dimension. ICML Carl-Johann Simon-Gabriel, Yann Ollivier, Léon Bottou, Bernhard Schölkopf, David Lopez-Paz
2019	—	`conf`	Learning with Random Learning Rates. ECML/PKDD (2) Léonard Blier, Pierre Wolinski, Yann Ollivier
2019	A*	`conf`	Making Deep Q-learning methods robust to time discretization. ICML Corentin Tallec, Léonard Blier, Yann Ollivier
2019	J	`jnl`	Making Deep Q-learning methods robust to time discretization. CoRR Corentin Tallec, Léonard Blier, Yann Ollivier
2019	A*	`conf`	Separable value functions across time-scales. ICML Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Joelle Pineau, Emma Brunskill
2019	J	`jnl`	Separating value functions across time-scales. CoRR Joshua Romoff, Peter Henderson, Ahmed Touati, Yann Ollivier, Emma Brunskill, Joelle Pineau
2019	A*	`conf`	White-box vs Black-box: Bayes Optimal Strategies for Membership Inference. ICML Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid, Yann Ollivier, Hervé Jégou
2019	J	`jnl`	White-box vs Black-box: Bayes Optimal Strategies for Membership Inference. CoRR Alexandre Sablayrolles, Matthijs Douze, Yann Ollivier, Cordelia Schmid, Hervé Jégou
2018	J	`jnl`	Adversarial Vulnerability of Neural Networks Increases With Input Dimension. CoRR Carl-Johann Simon-Gabriel, Yann Ollivier, Bernhard Schölkopf, Léon Bottou, David Lopez-Paz
2018	J	`jnl`	Approximate Temporal Difference Learning is a Gradient Descent for Reversible Policies. CoRR Yann Ollivier
2018	—	`conf`	Can recurrent neural networks warp time? ICLR (Poster) Corentin Tallec, Yann Ollivier
2018	J	`jnl`	Can recurrent neural networks warp time? CoRR Corentin Tallec, Yann Ollivier
2018	J	`jnl`	Do Deep Learning Models Have Too Many Parameters? An Information Theory Viewpoint. CoRR Léonard Blier, Yann Ollivier
2018	J	`jnl`	Learning with Random Learning Rates. CoRR Léonard Blier, Pierre Wolinski, Yann Ollivier
2018	A*	`conf`	Mixed batches and symmetric discriminators for GAN training. ICML Thomas Lucas, Corentin Tallec, Yann Ollivier, Jakob Verbeek
2018	J	`jnl`	Mixed batches and symmetric discriminators for GAN training. CoRR Thomas Lucas, Corentin Tallec, Jakob Verbeek, Yann Ollivier
2018	A*	`conf`	The Description Length of Deep Learning models. NeurIPS Léonard Blier, Yann Ollivier
2018	—	`conf`	Unbiased Online Recurrent Optimization. ICLR (Poster) Corentin Tallec, Yann Ollivier
2017	J	`jnl`	Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles. J. Mach. Learn. Res. Yann Ollivier, Ludovic Arnold, Anne Auger, Nikolaus Hansen
2017	—	`conf`	Natural Langevin Dynamics for Neural Networks. GSI Gaétan Marceau-Caron, Yann Ollivier
2017	J	`jnl`	Natural Langevin Dynamics for Neural Networks. CoRR Gaétan Marceau-Caron, Yann Ollivier
2017	J	`jnl`	True Asymptotic Natural Gradient Optimization. CoRR Yann Ollivier
2017	J	`jnl`	Unbiased Online Recurrent Optimization. CoRR Corentin Tallec, Yann Ollivier
2017	J	`jnl`	Unbiasing Truncated Backpropagation Through Time. CoRR Corentin Tallec, Yann Ollivier
2016	J	`jnl`	Practical Riemannian Neural Networks. CoRR Gaétan Marceau-Caron, Yann Ollivier
2015	—	`conf`	Laplace's Rule of Succession in Information Geometry. GSI Yann Ollivier
2015	J	`jnl`	Laplace's rule of succession in information geometry. CoRR Yann Ollivier
2015	J	`jnl`	Speed learning on the fly. CoRR Pierre-Yves Massé, Yann Ollivier
2015	J	`jnl`	Training recurrent networks online without backtracking. CoRR Yann Ollivier, Guillaume Charpiat
2014	J	`jnl`	Auto-encoders: reconstruction versus compression. CoRR Yann Ollivier
2014	—	`book`	Optimal Transport - Theory and Applications. Optimal Transport Yann Ollivier, Herve Pajot, Cédric Villani
2013	—	`conf`	Information-Geometric Optimization: The Interest of Information Theory for Discrete and Continuous Optimization. GSI Yann Ollivier
2013	A	`conf`	Objective improvement in information-geometric optimization. FOGA Youhei Akimoto, Yann Ollivier
2013	J	`jnl`	Persistent Contextual Neural Networks for learning symbolic data sequences. CoRR Yann Ollivier
2013	J	`jnl`	Riemannian metrics for neural networks CoRR Yann Ollivier
2012	J	`jnl`	A Curved Brunn-Minkowski Inequality on the Discrete Hypercube, Or: What Is the Ricci Curvature of the Discrete Hypercube? SIAM J. Discret. Math. Yann Ollivier, Cédric Villani
2012	J	`jnl`	Layer-wise learning of deep generative models CoRR Ludovic Arnold, Yann Ollivier
2012	J	`jnl`	Objective Improvement in Information-Geometric Optimization CoRR Youhei Akimoto, Yann Ollivier
2007	A*	`conf`	Finding Related Pages Using Green Measures: An Illustration with Wikipedia. AAAI Yann Ollivier, Pierre Senellart
2007	J	`jnl`	Some Small Cancellation Properties of Random Groups. Int. J. Algebra Comput. Yann Ollivier
2003	J	`jnl`	Rate of convergence of crossover operators. Random Struct. Algorithms Yann Ollivier