DiscoGen: Learning to Discover Gene Regulatory Networks

no code implementations • 12 Apr 2023 • Nan Rosemary Ke, Sara-Jane Dunn, Jorg Bornschein, Silvia Chiappa, Melanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane Wang, Theophane Weber, David Barrett, Matthew Botvinick, Anirudh Goyal, Mike Mozer, Danilo Rezende

To accurately identify GRNs, perturbational data is required.

Causal Discovery

Learning to Induce Causal Structure

no code implementations • 11 Apr 2022 • Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Anirudh Goyal, Jorg Bornschein, Melanie Rey, Theophane Weber, Matthew Botvinic, Michael Mozer, Danilo Jimenez Rezende

The fundamental challenge in causal induction is to infer the underlying graph structure given observational and/or interventional data.

Less can be more in contrastive learning

no code implementations • NeurIPS Workshop ICBINB 2020 • Jovana Mitrovic, Brian McWilliams, Melanie Rey

Usually the other datapoints in the batch serve as the negatives for the given datapoint.

Contrastive Learning Representation Learning

Meta-Gaussian Information Bottleneck

no code implementations • NeurIPS 2012 • Melanie Rey, Volker Roth

We present a reformulation of the information bottleneck (IB) problem in terms of copula, using the equivalence between mutual information and negative copula entropy.