23 citations · 79 across the 6 of their papers we have counts for
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cs.LG2021★ 23 cited
Causal Reinforcement Learning using Observational and Interventional Data
Maxime Gasse, Damien Grasset, Guillaume Gaudron +1
Learning efficiently a causal model of the environment is a key challenge of model-based RL agents operating in POMDPs. We consider here a scenario where the learning agent has the…
cs.LG2021★ 1 cited
Ecole: A Library for Learning Inside MILP Solvers
Antoine Prouvost, Justin Dumouchelle, Maxime Gasse +2
In this paper we describe Ecole (Extensible Combinatorial Optimization Learning Environments), a library to facilitate integration of machine learning in combinatorial optimization…