Search Results for author: Mathieu Chalvidal

Found 6 papers, 3 papers with code

Learning Functional Transduction

no code implementations1 Feb 2023 Mathieu Chalvidal, Thomas Serre, Rufin VanRullen

Research in Machine Learning has polarized into two general regression approaches: Transductive methods derive estimates directly from available data but are usually problem unspecific.

Meta-Reinforcement Learning with Self-Modifying Networks

no code implementations4 Feb 2022 Mathieu Chalvidal, Thomas Serre, Rufin VanRullen

Deep Reinforcement Learning has demonstrated the potential of neural networks tuned with gradient descent for solving complex tasks in well-delimited environments.

Meta Reinforcement Learning One-Shot Learning +2

KuraNet: Systems of Coupled Oscillators that Learn to Synchronize

1 code implementation6 May 2021 Matthew Ricci, Minju Jung, Yuwei Zhang, Mathieu Chalvidal, Aneri Soni, Thomas Serre

Here, we present a single approach to both of these problems in the form of "KuraNet", a deep-learning-based system of coupled oscillators that can learn to synchronize across a distribution of disordered network conditions.

Go with the Flow: Adaptive Control for Neural ODEs

no code implementations ICLR 2021 Mathieu Chalvidal, Matthew Ricci, Rufin VanRullen, Thomas Serre

Despite their elegant formulation and lightweight memory cost, neural ordinary differential equations (NODEs) suffer from known representational limitations.

Image Reconstruction Representation Learning

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