Synbols: Probing Learning Algorithms with Synthetic Datasets

Synbols: Probing Learning Algorithms with Synthetic Datasets

14 September 2020

Alexandre Lacoste

Frederic Branchaud-Charron

Parmida Atighehchian

Alexandre Drouin

Laurent Charlin

David Vázquez

Papers citing "Synbols: Probing Learning Algorithms with Synthetic Datasets"

6 / 6 papers shown

Title
Implicit Visual Bias Mitigation by Posterior Estimate Sharpening of a Bayesian Neural Network Rebecca S Stone Nishant Ravikumar A. Bulpitt David C. Hogg BDL 36 0 0 29 Mar 2023
Can Active Learning Preemptively Mitigate Fairness Issues? Frederic Branchaud-Charron Parmida Atighehchian Pau Rodríguez Grace Abuhamad Alexandre Lacoste FaML 22 20 0 14 Apr 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 34 55 0 18 Mar 2021
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 329 11,681 0 09 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015