Skip-Thought Memory Networks. - Ethan Caballero (CoRR, 2015)

In search of robust measures of generalization. - Gintare Karolina Dziugaite; Alexandre Drouin; Brady Neal; Nitarshan Rajkumar; Ethan Caballero; Linbo Wang 003; Ioannis Mitliagkas; Daniel M. Roy 001 (NeurIPS, 2020)

Out-of-Distribution Generalization via Risk Extrapolation (REx). - David Krueger 001; Ethan Caballero; Jörn-Henrik Jacobsen; Amy Zhang 001; Jonathan Binas; Rémi Le Priol; Aaron C. Courville (CoRR, 2020)

Out-of-Distribution Generalization via Risk Extrapolation (REx). - David Krueger 001; Ethan Caballero; Jörn-Henrik Jacobsen; Amy Zhang 001; Jonathan Binas; Dinghuai Zhang; Rémi Le Priol; Aaron C. Courville (ICML, 2021)

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. - Kartik Ahuja; Ethan Caballero; Dinghuai Zhang; Jean-Christophe Gagnon-Audet; Yoshua Bengio; Ioannis Mitliagkas; Irina Rish (NeurIPS, 2021)

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization. - Kartik Ahuja; Ethan Caballero; Dinghuai Zhang; Yoshua Bengio; Ioannis Mitliagkas; Irina Rish (CoRR, 2021)

Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers. - Gabriele Prato 001; Simon Guiroy; Ethan Caballero; Irina Rish; Sarath Chandar (CoRR, 2021)

Broken Neural Scaling Laws. - Ethan Caballero; Kshitij Gupta; Irina Rish; David Krueger 001 (ICLR, 2023)