258 citations
- Laboratoire Angevin de Recherche en MathématiquesFR198 papers
- Centre National de la Recherche ScientifiqueFR127 papers
- Institut des Sciences et Technologies Moléculaires d'AngersFR31 papers
- Sorbonne UniversitéFR17 papers
- Wrocław University of Science and TechnologyPL17 papers
- Institut de Mathématiques de ToulouseFR13 papers
- Institute for Theoretical and Experimental PhysicsRU12 papers
- Université Paris-SaclayFR12 papers
- Université Toulouse III - Paul SabatierFR12 papers
- Horia Hulubei National Institute for R and D in Physics and Nuclear EngineeringRO10 papers
- Institut d'électronique de microélectronique et de nanotechnologieFR10 papers
- Université Nantes Angers Le MansFR10 papers
10 papers · 1 filter
Guiding Evolutionary Molecular Design: Adding Reinforcement Learning for Mutation Selection
Gaelle Milon-Harnois, Chaimaa Touhami, Nicolas Gutowski +2
The efficient exploration of chemical space remains a central challenge, as many generative models still produce unstable or non-synthesizable compounds. To address these limitatio…
A Transformer Model for Predicting Chemical Products from Generic SMARTS Templates with Data Augmentation
Derin Ozer, Sylvain Lamprier, Thomas Cauchy +2
The accurate prediction of chemical reaction outcomes is a major challenge in computational chemistry. Current models rely heavily on either highly specific reaction templates or t…
Reinforcement Learning for Aligning Large Language Models Agents with Interactive Environments: Quantifying and Mitigating Prompt Overfitting
Mohamed Salim Aissi, Clement Romac, Thomas Carta +5
Reinforcement learning (RL) is a promising approach for aligning large language models (LLMs) knowledge with sequential decision-making tasks. However, few studies have thoroughly…
Robust Deep Reinforcement Learning Through Adversarial Attacks and Training : A Survey
Lucas Schott, Josephine Delas, Hatem Hajri +5
Deep Reinforcement Learning (DRL) is a subfield of machine learning for training autonomous agents that take sequential actions across complex environments. Despite its significant…
Deinterleaving of Discrete Renewal Process Mixtures with Application to Electronic Support Measures
Jean Pinsolle, Olivier Goudet, Cyrille Enderli +2
In this paper, we propose a new deinterleaving method for mixtures of discrete renewal Markov chains. This method relies on the maximization of a penalized likelihood score. It exp…
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing
Vincent Grari, Thibault Laugel, Tatsunori Hashimoto +2
In the field of algorithmic fairness, significant attention has been put on group fairness criteria, such as Demographic Parity and Equalized Odds. Nevertheless, these objectives,…