Carles Domingo-Enrich

According to our database, Carles Domingo-Enrich authored at least 26 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Trust Region Constrained Measure Transport in Path Space for Stochastic Optimal Control and Inference.

Denis Blessing, Julius Berner, Lorenz Richter, Carles Domingo-Enrich, Yuanqi Du, Arash Vahdat, Gerhard Neumann

CoRR, August, 2025

Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching.

Aaron J. Havens, Benjamin Kurt Miller, Bing Yan, Carles Domingo-Enrich, Anuroop Sriram, Brandon M. Wood, Daniel Levine, Bin Hu, Brandon Amos, Brian Karrer, Xiang Fu, Guan-Horng Liu, Ricky T. Q. Chen

CoRR, April, 2025

Conditioning Diffusions Using Malliavin Calculus.

Jakiw Pidstrigach, Elizabeth Baker, Carles Domingo-Enrich, George Deligiannidis, Nikolas Nüsken

CoRR, April, 2025

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Generative modeling and Stochastic Control as Dynamics on Probability Distributions

Carles Domingo-Enrich

PhD thesis, 2024

A Taxonomy of Loss Functions for Stochastic Optimal Control.

Carles Domingo-Enrich

CoRR, 2024

Neural Optimal Transport with Lagrangian Costs.

Aram-Alexandre Pooladian, Carles Domingo-Enrich, Ricky T. Q. Chen, Brandon Amos

Proceedings of the Uncertainty in Artificial Intelligence, 2024

Stochastic Optimal Control Matching.

Carles Domingo-Enrich, Jiequn Han, Brandon Amos, Joan Bruna, Ricky T. Q. Chen

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

An Explicit Expansion of the Kullback-Leibler Divergence along its Fisher-Rao Gradient Flow.

Carles Domingo-Enrich, Aram-Alexandre Pooladian

Trans. Mach. Learn. Res., 2023

Length Generalization in Arithmetic Transformers.

Samy Jelassi, Stéphane d'Ascoli, Carles Domingo-Enrich, Yuhuai Wu, Yuanzhi Li, François Charton

CoRR, 2023

Open Problem: Learning with Variational Objectives on Measures.

Vivien Cabannes, Carles Domingo-Enrich

CoRR, 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

Proceedings of the International Conference on Machine Learning, 2023

Learning with Stochastic Orders.

Carles Domingo-Enrich, Yair Schiff, Youssef Mroueh

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Compress Then Test: Powerful Kernel Testing in Near-linear Time.

Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Computing the Variance of Shuffling Stochastic Gradient Algorithms via Power Spectral Density Analysis.

Carles Domingo-Enrich

CoRR, 2022

Auditing Differential Privacy in High Dimensions with the Kernel Quantum Rényi Divergence.

Carles Domingo-Enrich, Youssef Mroueh

CoRR, 2022

Tighter Sparse Approximation Bounds for ReLU Neural Networks.

Carles Domingo-Enrich, Youssef Mroueh

Proceedings of the Tenth International Conference on Learning Representations, 2022

Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators.

Carles Domingo-Enrich

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks.

Carles Domingo-Enrich, Alberto Bietti, Marylou Gabrié, Joan Bruna, Eric Vanden-Eijnden

CoRR, 2021

Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics.

Carles Domingo-Enrich, Youssef Mroueh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Energy-Based Models with Overparametrized Shallow Neural Networks.

Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna

Proceedings of the 38th International Conference on Machine Learning, 2021

Average-case Acceleration for Bilinear Games and Normal Matrices.

Carles Domingo-Enrich, Fabian Pedregosa, Damien Scieur

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

A mean-field analysis of two-player zero-sum games.

Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Extra-gradient with player sampling for faster convergence in n-player games.

Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Extra-gradient with player sampling for provable fast convergence in n-player games.

Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna

CoRR, 2019

2018

Outsourcing scalar products and matrix products on privacy-protected unencrypted data stored in untrusted clouds.

Josep Domingo-Ferrer, Sara Ricci, Carles Domingo-Enrich

Inf. Sci., 2018