Preprints & Publications
Preprints
- Towards deep learning sequence-structure co-generation for protein design
Chentong Wang, Sarah Alamdari, Carles Domingo-Enrich, Ava Amini, Kevin K. Yang Oct. 2024 - A taxonomy of loss functions for stochastic optimal control
Carles Domingo-Enrich. Oct. 2024 - Adjoint matching: fine-tuning flow and diffusion generative models with memoryless stochastic optimal control
Carles Domingo-Enrich, Michal Drozdzal, Brian Karrer, Ricky T. Q. Chen. Sept. 2024 - Length generalization in arithmetic transformers
Samy Jelassi, Stéphane d’Ascoli, Carles Domingo-Enrich, Yuhuai Wu, Yuanzhi Li, François Charton. Jun. 2023 - Open problem: learning with variational objectives on measures
Vivien Cabannes, Carles Domingo-Enrich. Jun. 2023 - Computing the variance of shuffling stochastic gradient algorithms via power spectral density analysis
Carles Domingo-Enrich. Jun. 2022 - Auditing differential privacy in high dimensions with the kernel quantum Rényi divergence
Carles Domingo-Enrich, Youssef Mroueh. May 2022 - Simultaneous transport evolution for minimax equilibria on measures
Carles Domingo-Enrich, Joan Bruna. Feb. 2022 - Dual training of energy-based models with overparametrized shallow neural networks
Carles Domingo-Enrich, Alberto Bietti, Marylou Gabrié, Joan Bruna, Eric Vanden-Eijnden. July 2021
Publications
- Stochastic optimal control matching
Carles Domingo-Enrich, Jiequn Han, Brandon Amos, Joan Bruna, Ricky T. Q. Chen. NeurIPS 2024 - Neural optimal transport with Lagrangian costs
Aram-Alexandre Pooladian, Carles Domingo-Enrich, Ricky T. Q. Chen, Brandon Amos. UAI, 2024 - An explicit expansion of the Kullback-Leibler divergence along its Fisher-Rao gradient flow
Carles Domingo-Enrich, Aram-Alexandre Pooladian. TMLR 2023 - Multisample Flow Matching: straightening flows with minibatch couplings
Aram-Alexandre Pooladian*, Heli Ben-Hamu*, Carles Domingo-Enrich*, Brandon Amos, Yaron Lipman, Ricky T. Q. Chen (*Equal contribution). ICML 2023 - Compress Then Test: powerful kernel testing in near-linear time
Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey. AISTATS 2023 - Learning with stochastic orders
Carles Domingo-Enrich, Yair Schiff, Youssef Mroueh. ICLR 2023 - Depth and feature learning are provably beneficial for neural network discriminators
Carles Domingo-Enrich. COLT 2022 - Tighter sparse approximation bounds for ReLU neural networks
Carles Domingo-Enrich, Youssef Mroueh. ICLR 2022, Spotlight. - Separation results between fixed-kernel and feature-learning probability metrics
Carles Domingo-Enrich, Youssef Mroueh. NeurIPS 2021, Oral. - On energy-based models with overparametrized shallow neural networks
Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna. ICML 2021, Long talk. - Average-case acceleration for bilinear games and normal matrices
Carles Domingo-Enrich, Damien Scieur, Fabian Pedregosa. ICLR 2021 - A mean-field analysis of two-player zero-sum games
Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna. NeurIPS 2020 - Extra-gradient with player sampling for faster Nash equilibrium finding
Samy Jelassi*, Carles Domingo-Enrich*, Damien Scieur, Arthur Mensch, Joan Bruna (*Equal contribution). ICML 2020 - Outsourcing scalar products and matrix products on privacy-protected unencrypted data stored in untrusted clouds
Josep Domingo-Ferrer, Sara Ricci, Carles Domingo-Enrich. Information Sciences, Vol. 436, pp. 320-342, Apr 2018
