13 citations · 14 across the 3 of their papers we have counts for
3 papers
Optimality Inductive Biases and Agnostic Guidelines for Offline Reinforcement Learning
Lionel Blondé, Alexandros Kalousis, Stéphane Marchand-Maillet
The performance of state-of-the-art offline RL methods varies widely over the spectrum of dataset qualities, ranging from far-from-optimal random data to close-to-optimal expert de…
Learning Interpretable Microscopic Features of Tumor by Multi-task Adversarial CNNs To Improve Generalization
Mara Graziani, Sebastian Otalora, Stephane Marchand-Maillet +2
Adopting Convolutional Neural Networks (CNNs) in the daily routine of primary diagnosis requires not only near-perfect precision, but also a sufficient degree of generalization to…
Adjacency and Tensor Representation in General Hypergraphs Part 1: e-adjacency Tensor Uniformisation Using Homogeneous Polynomials
Xavier Ouvrard, Jean-Marie Le Goff, Stéphane Marchand-Maillet
Adjacency between two vertices in graphs or hypergraphs is a pairwise relationship. It is redefined in this article as 2-adjacency. In general hypergraphs, hyperedges hold for -…