Invariance Principle Meets Information Bottleneck for
Out-of-Distribution Generalization

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization

11 June 2021

Ethan Caballero

Jean-Christophe Gagnon-Audet

Ioannis Mitliagkas

Papers citing "Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization"

6 / 56 papers shown

Title
Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much Bryan D. He Christopher De Sa Ioannis Mitliagkas Christopher Ré 17 41 0 10 Jun 2016
The deterministic information bottleneck D. Strouse D. Schwab 15 134 0 01 Apr 2016
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 318 9,418 0 28 May 2015
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 74 961 0 06 Jan 2015
Domain Generalization via Invariant Feature Representation Krikamol Muandet David Balduzzi Bernhard Schölkopf OOD 64 1,166 0 10 Jan 2013
On Causal and Anticausal Learning Bernhard Schölkopf Dominik Janzing J. Peters Eleni Sgouritsa Kun Zhang Joris Mooij CML 57 604 0 27 Jun 2012