32 citations · 72 across the 9 of their papers we have counts for
9 papers
Surfer 2: The Next Generation of Cross-Platform Computer Use Agents
Mathieu Andreux, Märt Bakler, Yanael Barbier +50
Building agents that generalize across web, desktop, and mobile environments remains an open challenge, as prior systems rely on environment-specific interfaces that limit cross-pl…
PASTA: Pretrained Action-State Transformer Agents
Raphael Boige, Yannis Flet-Berliac, Arthur Flajolet +2
Self-supervised learning has brought about a revolutionary paradigm shift in various computing domains, including NLP, vision, and biology. Recent approaches involve pre-training t…
Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces
Raphael Boige, Guillaume Richard, Jérémie Dona +2
Quality Diversity (QD) algorithms have been proposed to search for a large collection of both diverse and high-performing solutions instead of a single set of local optima. While e…
The Quality-Diversity Transformer: Generating Behavior-Conditioned Trajectories with Decision Transformers
Valentin Macé, Raphaël Boige, Felix Chalumeau +3
In the context of neuroevolution, Quality-Diversity algorithms have proven effective in generating repertoires of diverse and efficient policies by relying on the definition of a b…
Multi-Objective Quality Diversity Optimization
Thomas Pierrot, Guillaume Richard, Karim Beguir +1
In this work, we consider the problem of Quality-Diversity (QD) optimization with multiple objectives. QD algorithms have been proposed to search for a large collection of both div…
Unsupervised Domain Adaptation for Constraining Star Formation Histories
Sankalp Gilda, Antoine de Mathelin, Sabine Bellstedt +1
The prevalent paradigm of machine learning today is to use past observations to predict future ones. What if, however, we are interested in knowing the past given the present? This…
ADAPT : Awesome Domain Adaptation Python Toolbox
Antoine de Mathelin, Mounir Atiq, Guillaume Richard +5
In this paper, we introduce the ADAPT library, an open source Python API providing the implementation of the main transfer learning and domain adaptation methods. The library is de…
Adversarial Weighting for Domain Adaptation in Regression
Antoine de Mathelin, Guillaume Richard, Francois Deheeger +2
We present a novel instance-based approach to handle regression tasks in the context of supervised domain adaptation under an assumption of covariate shift. The approach developed…
Autoencoder-based time series clustering with energy applications
Guillaume Richard, Benoît Grossin, Guillaume Germaine +2
Time series clustering is a challenging task due to the specific nature of the data. Classical approaches do not perform well and need to be adapted either through a new distance m…