Adversarial Divergences are Good Task Losses for Generative Modeling. - Gabriel Huang; Gauthier Gidel; Hugo Berard; Ahmed Touati; Simon Lacoste-Julien (CoRR, 2017)

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling. - Gabriel Huang; Hugo Berard; Ahmed Touati; Gauthier Gidel; Pascal Vincent; Simon Lacoste-Julien (ICLR (Workshop), 2018)

A Variational Inequality Perspective on Generative Adversarial Nets. - Gauthier Gidel; Hugo Berard; Pascal Vincent; Simon Lacoste-Julien (CoRR, 2018)

A Variational Inequality Perspective on Generative Adversarial Networks. - Gauthier Gidel; Hugo Berard; Gaëtan Vignoud; Pascal Vincent; Simon Lacoste-Julien (ICLR (Poster), 2019)

A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. - Hugo Berard; Gauthier Gidel; Amjad Almahairi; Pascal Vincent; Simon Lacoste-Julien (ICLR, 2020)

Stochastic Hamiltonian Gradient Methods for Smooth Games. - Nicolas Loizou; Hugo Berard; Alexia Jolicoeur-Martineau; Pascal Vincent; Simon Lacoste-Julien; Ioannis Mitliagkas (ICML, 2020)

Adversarial Example Games. - Avishek Joey Bose; Gauthier Gidel; Hugo Berard; Andre Cianflone; Pascal Vincent; Simon Lacoste-Julien; William L. Hamilton (NeurIPS, 2020)

Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. - Nicolas Loizou; Hugo Berard; Gauthier Gidel; Ioannis Mitliagkas; Simon Lacoste-Julien (NeurIPS, 2021)

Stochastic Extragradient: General Analysis and Improved Rates. - Eduard Gorbunov; Hugo Berard; Gauthier Gidel; Nicolas Loizou (AISTATS, 2022)

Online Adversarial Attacks. - Andjela Mladenovic; Avishek Joey Bose; Hugo Berard; William L. Hamilton; Simon Lacoste-Julien; Pascal Vincent; Gauthier Gidel (ICLR, 2022)

Stochastic Gradient Descent-Ascent: Unified Theory and New Efficient Methods. - Aleksandr Beznosikov; Eduard Gorbunov; Hugo Berard; Nicolas Loizou (AISTATS, 2023)

From Efficiency to Equity: Measuring Fairness in Preference Learning. - Shreeyash Gowaikar; Hugo Berard; Rashid Mushkani; Shin Koseki (CoRR, 2024)

AI-EDI-SPACE: A Co-designed Dataset for Evaluating the Quality of Public Spaces. - Shreeyash Gowaikar; Hugo Berard; Rashid Mushkani; Emmanuel Beaudry Marchand; Toumadher Ammar; Shin Koseki (CoRR, 2024)

The Right to AI. - Rashid Mushkani; Hugo Berard; Allison Cohen; Shin Koeski (CoRR, 2025)

LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces. - Rashid Mushkani; Shravan Nayak; Hugo Berard; Allison Cohen; Shin Koseki; Hadrien Bertrand (CoRR, 2025)

Negotiative Alignment: Embracing Disagreement to Achieve Fairer Outcomes - Insights from Urban Studies. - Rashid Mushkani; Hugo Berard; Shin Koseki (CoRR, 2025)