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20162025
most citedA Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms

122 citations · 287 across the 27 of their papers we have counts for

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Showing 2019 · cs.LGShow all

5 papers · 2 filters

cs.LG2019★ 6 cited

The TCGA Meta-Dataset Clinical Benchmark

Mandana Samiei, Tobias Würfl, Tristan Deleu +6

Machine learning is bringing a paradigm shift to healthcare by changing the process of disease diagnosis and prognosis in clinics and hospitals. This development equips doctors and…

cs.LG2019

Torchmeta: A Meta-Learning library for PyTorch

Tristan Deleu, Tobias Würfl, Mandana Samiei +2

The constant introduction of standardized benchmarks in the literature has helped accelerating the recent advances in meta-learning research. They offer a way to get a fair compari…

cs.LG2019★ 3 cited

Learning Powerful Policies by Using Consistent Dynamics Model

Shagun Sodhani, Anirudh Goyal, Tristan Deleu +3

Model-based Reinforcement Learning approaches have the promise of being sample efficient. Much of the progress in learning dynamics models in RL has been made by learning models vi…

cs.LG2019

Gradient-Based Neural DAG Learning

Sébastien Lachapelle, Philippe Brouillard, Tristan Deleu +1

We propose a novel score-based approach to learning a directed acyclic graph (DAG) from observational data. We adapt a recently proposed continuous constrained optimization formula…

cs.LG2019★ 122 cited

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms

Yoshua Bengio, Tristan Deleu, Nasim Rahaman +5

We propose to meta-learn causal structures based on how fast a learner adapts to new distributions arising from sparse distributional changes, e.g. due to interventions, actions of…