GANGs: Generative Adversarial Network Games. - Frans A. Oliehoek; Rahul Savani; Jose Gallego-Posada; Elise van der Pol; Edwin D. de Jong; Roderich Gross (CoRR, 2017)

Beyond Local Nash Equilibria for Adversarial Networks. - Frans A. Oliehoek; Rahul Savani; Jose Gallego-Posada; Elise van der Pol; Roderich Groß (BNCAI, 2018)

GEAR: Geometry-Aware Rényi Information. - Jose Gallego-Posada; Ankit Vani; Max Schwarzer; Simon Lacoste-Julien (CoRR, 2019)

GAIT: A Geometric Approach to Information Theory. - Jose Gallego-Posada; Ankit Vani; Max Schwarzer; Simon Lacoste-Julien (AISTATS, 2020)

Controlled Sparsity via Constrained Optimization or: How I Learned to Stop Tuning Penalties and Love Constraints. - Jose Gallego-Posada; Juan Ramirez; Akram Erraqabi; Yoshua Bengio; Simon Lacoste-Julien (NeurIPS, 2022)

L0onie: Compressing COINs with L0-constraints. - Juan Ramirez; Jose Gallego-Posada (CoRR, 2022)

Equivariant Mesh Attention Networks. - Sourya Basu; Jose Gallego-Posada; Francesco Viganò; James Rowbottom; Taco Cohen (Trans. Mach. Learn. Res., 2022)

A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale. - Hao-Jun Michael Shi; Tsung-Hsien Lee; Shintaro Iwasaki; Jose Gallego-Posada; Zhijing Li 001; Kaushik Rangadurai; Dheevatsa Mudigere; Michael Rabbat (CoRR, 2023)

Balancing Act: Constraining Disparate Impact in Sparse Models. - Meraj Hashemizadeh; Juan Ramirez; Rohan Sukumaran; Golnoosh Farnadi; Simon Lacoste-Julien; Jose Gallego-Posada (ICLR, 2024)

On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization. - Motahareh Sohrabi; Juan Ramirez; Tianyue H. Zhang; Simon Lacoste-Julien; Jose Gallego-Posada (ICML, 2024)

Feasible Learning. - Juan Ramirez; Ignacio Hounie; Juan Elenter; Jose Gallego-Posada; Meraj Hashemizadeh; Alejandro Ribeiro; Simon Lacoste-Julien (AISTATS, 2025)

Cooper: A Library for Constrained Optimization in Deep Learning. - Jose Gallego-Posada; Juan Ramirez; Meraj Hashemizadeh; Simon Lacoste-Julien (CoRR, 2025)