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ORCIDCarles Domingo-Enrich
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Journal Articles
- 2023
[j2]Carles Domingo-Enrich, Aram-Alexandre Pooladian:
An Explicit Expansion of the Kullback-Leibler Divergence along its Fisher-Rao Gradient Flow. Trans. Mach. Learn. Res. 2023 (2023)- 2018
- [j1]Josep Domingo-Ferrer
, Sara Ricci, Carles Domingo-Enrich:
Outsourcing scalar products and matrix products on privacy-protected unencrypted data stored in untrusted clouds. Inf. Sci. 436-437: 320-342 (2018)
Conference and Workshop Papers
- 2023
- [c10]Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey:
Compress Then Test: Powerful Kernel Testing in Near-linear Time. AISTATS 2023: 1174-1218 - [c9]Carles Domingo-Enrich, Yair Schiff, Youssef Mroueh:
Learning with Stochastic Orders. ICLR 2023 - [c8]Aram-Alexandre Pooladian, Heli Ben-Hamu, Carles Domingo-Enrich, Brandon Amos, Yaron Lipman, Ricky T. Q. Chen:
Multisample Flow Matching: Straightening Flows with Minibatch Couplings. ICML 2023: 28100-28127 - 2022
- [c7]Carles Domingo-Enrich:
Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators. COLT 2022: 421-447 - [c6]Carles Domingo-Enrich, Youssef Mroueh:
Tighter Sparse Approximation Bounds for ReLU Neural Networks. ICLR 2022 - 2021
- [c5]Carles Domingo-Enrich, Fabian Pedregosa, Damien Scieur:
Average-case Acceleration for Bilinear Games and Normal Matrices. ICLR 2021 - [c4]Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna:
On Energy-Based Models with Overparametrized Shallow Neural Networks. ICML 2021: 2771-2782 - [c3]Carles Domingo-Enrich, Youssef Mroueh:
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics. NeurIPS 2021: 19248-19260 - 2020
- [c2]Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna:
Extra-gradient with player sampling for faster convergence in n-player games. ICML 2020: 4736-4745 - [c1]Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna:
A mean-field analysis of two-player zero-sum games. NeurIPS 2020
Informal and Other Publications
- 2024
- [i18]Aram-Alexandre Pooladian, Carles Domingo-Enrich, Ricky T. Q. Chen, Brandon Amos:
Neural Optimal Transport with Lagrangian Costs. CoRR abs/2406.00288 (2024) - [i17]Carles Domingo-Enrich, Michal Drozdzal, Brian Karrer, Ricky T. Q. Chen:
Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control. CoRR abs/2409.08861 (2024) - 2023
- [i16]Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey:
Compress Then Test: Powerful Kernel Testing in Near-linear Time. CoRR abs/2301.05974 (2023) - [i15]Aram-Alexandre Pooladian, Heli Ben-Hamu, Carles Domingo-Enrich, Brandon Amos, Yaron Lipman, Ricky T. Q. Chen:
Multisample Flow Matching: Straightening Flows with Minibatch Couplings. CoRR abs/2304.14772 (2023) - [i14]Vivien Cabannes, Carles Domingo-Enrich:
Open Problem: Learning with Variational Objectives on Measures. CoRR abs/2306.11928 (2023) - [i13]Samy Jelassi, Stéphane d'Ascoli, Carles Domingo-Enrich, Yuhuai Wu, Yuanzhi Li, François Charton:
Length Generalization in Arithmetic Transformers. CoRR abs/2306.15400 (2023) - [i12]Carles Domingo-Enrich, Jiequn Han, Brandon Amos, Joan Bruna, Ricky T. Q. Chen:
Stochastic Optimal Control Matching. CoRR abs/2312.02027 (2023) - 2022
- [i11]Carles Domingo-Enrich, Yair Schiff, Youssef Mroueh:
Learning with Stochastic Orders. CoRR abs/2205.13684 (2022) - [i10]Carles Domingo-Enrich, Youssef Mroueh:
Auditing Differential Privacy in High Dimensions with the Kernel Quantum Rényi Divergence. CoRR abs/2205.13941 (2022) - [i9]Carles Domingo-Enrich:
Computing the Variance of Shuffling Stochastic Gradient Algorithms via Power Spectral Density Analysis. CoRR abs/2206.00632 (2022) - 2021
- [i8]Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna:
On Energy-Based Models with Overparametrized Shallow Neural Networks. CoRR abs/2104.07531 (2021) - [i7]Carles Domingo-Enrich, Youssef Mroueh:
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics. CoRR abs/2106.05739 (2021) - [i6]Carles Domingo-Enrich, Alberto Bietti, Marylou Gabrié, Joan Bruna, Eric Vanden-Eijnden:
Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks. CoRR abs/2107.05134 (2021) - [i5]Carles Domingo-Enrich, Youssef Mroueh:
Tighter Sparse Approximation Bounds for ReLU Neural Networks. CoRR abs/2110.03673 (2021) - [i4]Carles Domingo-Enrich:
Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators. CoRR abs/2112.13867 (2021) - 2020
- [i3]Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna:
A mean-field analysis of two-player zero-sum games. CoRR abs/2002.06277 (2020) - [i2]Carles Domingo-Enrich, Fabian Pedregosa, Damien Scieur:
Average-case Acceleration for Bilinear Games and Normal Matrices. CoRR abs/2010.02076 (2020) - 2019
- [i1]Samy Jelassi, Carles Domingo-Enrich, Damien Scieur, Arthur Mensch, Joan Bruna:
Extra-gradient with player sampling for provable fast convergence in n-player games. CoRR abs/1905.12363 (2019)
Coauthor Index
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