Ruben Ohana

According to our database, Ruben Ohana authored at least 30 papers between 2020 and 2026.

Collaborative distances:

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

2026

On the Value of Tokeniser Pretraining in Physics Foundation Models.

Hadi Sotoudeh, Payel Mukhopadhyay, Ruben Ohana, Michael McCabe, Neil D. Lawrence, Shirley Ho, Miles D. Cranmer

CoRR, March, 2026

2025

Predicting partially observable dynamical systems via diffusion models with a multiscale inference scheme.

Rudy Morel, Francesco Pio Ramunno, Jeff Shen, Alberto Bietti, Kyunghyun Cho, Miles D. Cranmer, Siavash Golkar, Olexandr Gugnin, Géraud Krawezik, Tanya Marwah, Michael McCabe, Lucas Meyer, Payel Mukhopadhyay, Ruben Ohana, Liam Holden Parker, Helen Qu, François Rozet, K. D. Leka, François Lanusse, David Fouhey, Shirley Ho

CoRR, November, 2025

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics.

Michael McCabe, Payel Mukhopadhyay, Tanya Marwah, Bruno Régaldo-Saint Blancard, François Rozet, Cristiana Diaconu, Lucas Meyer, Kaze W. K. Wong, Hadi Sotoudeh, Alberto Bietti, Irina Espejo, Rio Fear, Siavash Golkar, Tom Hehir, Keiya Hirashima, Géraud Krawezik, François Lanusse, Rudy Morel, Ruben Ohana, Liam Holden Parker, Mariel Pettee, Jeff Shen, Kyunghyun Cho, Miles D. Cranmer, Shirley Ho

CoRR, November, 2025

Universal Spectral Tokenization via Self-Supervised Panchromatic Representation Learning.

Jeff Shen, François Lanusse, Liam Holden Parker, Ollie Liu, Tom Hehir, Leopoldo Sarra, Lucas Meyer, Micah Bowles, Sebastian Wagner-Carena, Helen Qu, Siavash Golkar, Alberto Bietti, Hatim Bourfoune, Nathan Cassereau, Pierre Cornette, Keiya Hirashima, Géraud Krawezik, Ruben Ohana, Nicholas Lourie, Michael McCabe, Rudy Morel, Payel Mukhopadhyay, Mariel Pettee, Bruno Régaldo-Saint Blancard, Kyunghyun Cho, Miles D. Cranmer, Shirley Ho

CoRR, October, 2025

TC-LoRA: Temporally Modulated Conditional LoRA for Adaptive Diffusion Control.

Minkyoung Cho, Ruben Ohana, Christian Jacobsen, Adityan Jothi, Min-Hung Chen, Z. Morley Mao, Ethem Can

CoRR, October, 2025

Controllable Patching for Compute-Adaptive Surrogate Modeling of Partial Differential Equations.

Payel Mukhopadhyay, Michael McCabe, Ruben Ohana, Miles D. Cranmer

CoRR, July, 2025

Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation.

François Rozet, Ruben Ohana, Michael McCabe, Gilles Louppe, François Lanusse, Shirley Ho

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

AION-1: Omnimodal Foundation Model for Astronomical Sciences.

Liam Holden Parker, François Lanusse, Jeff Shen, Ollie Liu, Tom Hehir, Leopoldo Sarra, Lucas Meyer, Micah Bowles, Sebastian Wagner-Carena, Helen Qu, Siavash Golkar, Alberto Bietti, Hatim Bourfoune, Pierre Cornette, Keiya Hirashima, Géraud Krawezik, Ruben Ohana, Nicholas Lourie, Michael McCabe, Rudy Morel, Payel Mukhopadhyay, Mariel Pettee, Kyunghyun Cho, Miles D. Cranmer, Shirley Ho

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Optical training of large-scale Transformers and deep neural networks with direct feedback alignment.

Ziao Wang, Kilian Müller, Matthew J. Filipovich, Julien Launay, Ruben Ohana, Gustave Pariente, Safa Mokaadi, Charles Brossollet, Fabien Moreau, Alessandro Cappelli, Iacopo Poli, Igor Carron, Laurent Daudet, Florent Krzakala, Sylvain Gigan

CoRR, 2024

Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task.

Siavash Golkar, Alberto Bietti, Mariel Pettee, Michael Eickenberg, Miles D. Cranmer, Keiya Hirashima, Géraud Krawezik, Nicholas Lourie, Michael McCabe, Rudy Morel, Ruben Ohana, Liam Holden Parker, Bruno Régaldo-Saint Blancard, Kyunghyun Cho, Shirley Ho

CoRR, 2024

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning.

Ruben Ohana, Michael McCabe, Lucas Meyer, Rudy Morel, Fruzsina Julia Agocs, Miguel Beneitez, Marsha Berger, Blakesley Burkhart, Stuart B. Dalziel, Drummond B. Fielding, Daniel Fortunato, Jared A. Goldberg, Keiya Hirashima, Yan-Fei Jiang, Rich R. Kerswell, Suryanarayana Maddu, Jonah Miller, Payel Mukhopadhyay, Stefan S. Nixon, Jeff Shen, Romain Watteaux, Bruno Régaldo-Saint Blancard, François Rozet, Liam Holden Parker, Miles D. Cranmer, Shirley Ho

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Multiple Physics Pretraining for Spatiotemporal Surrogate Models.

Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Ruben Ohana, Miles D. Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Géraud Krawezik, François Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

MoMo: Momentum Models for Adaptive Learning Rates.

Fabian Schaipp, Ruben Ohana, Michael Eickenberg, Aaron Defazio, Robert M. Gower

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Listening to the noise: Blind Denoising with Gibbs Diffusion.

David Heurtel-Depeiges, Charles Margossian, Ruben Ohana, Bruno Régaldo-Saint Blancard

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Removing Dust from CMB Observations with Diffusion Models.

David Heurtel-Depeiges, Blakesley Burkhart, Ruben Ohana, Bruno Régaldo-Saint Blancard

CoRR, 2023

AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models.

François Lanusse, Liam Holden Parker, Siavash Golkar, Miles D. Cranmer, Alberto Bietti, Michael Eickenberg, Géraud Krawezik, Michael McCabe, Ruben Ohana, Mariel Pettee, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

CoRR, 2023

Multiple Physics Pretraining for Physical Surrogate Models.

Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Ruben Ohana, Miles D. Cranmer, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Géraud Krawezik, François Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

CoRR, 2023

xVal: A Continuous Number Encoding for Large Language Models.

Siavash Golkar, Mariel Pettee, Michael Eickenberg, Alberto Bietti, Miles D. Cranmer, Géraud Krawezik, François Lanusse, Michael McCabe, Ruben Ohana, Liam Holden Parker, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho

CoRR, 2023

Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein Distances.

Ruben Ohana, Kimia Nadjahi, Alain Rakotomamonjy, Liva Ralaivola

Proceedings of the International Conference on Machine Learning, 2023

Complex-to-Real Sketches for Tensor Products with Applications to the Polynomial Kernel.

Jonas Wacker, Ruben Ohana, Maurizio Filippone

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

2022

Complex-to-Real Random Features for Polynomial Kernels.

Jonas Wacker, Ruben Ohana, Maurizio Filippone

CoRR, 2022

Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients.

Alessandro Cappelli, Ruben Ohana, Julien Launay, Laurent Meunier, Iacopo Poli, Florent Krzakala

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients.

Alessandro Cappelli, Julien Launay, Laurent Meunier, Ruben Ohana, Iacopo Poli

CoRR, 2021

Photonic Differential Privacy with Direct Feedback Alignment.

Ruben Ohana, Hamlet Jesse Medina Ruiz, Julien Launay, Alessandro Cappelli, Iacopo Poli, Liva Ralaivola, Alain Rakotomamonjy

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

Align, then memorise: the dynamics of learning with feedback alignment.

Maria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt

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

Photonic co-processors in HPC: Using LightOn OPUs for Randomized Numerical Linear Algebra.

Daniel Hesslow, Alessandro Cappelli, Igor Carron, Laurent Daudet, Raphaël Lafargue, Kilian Müller, Ruben Ohana, Gustave Pariente, Iacopo Poli

Proceedings of the IEEE Hot Chips 33 Symposium, 2021

LightOn Optical Processing Unit : Scaling-up AI and HPC with a Non von Neumann co-processor.

Charles Brossollet, Alessandro Cappelli, Igor Carron, Charidimos Chaintoutis, Amélie Chatelain, Laurent Daudet, Sylvain Gigan, Daniel Hesslow, Florent Krzakala, Julien Launay, Safa Mokaadi, Fabien Moreau, Kilian Müller, Ruben Ohana, Gustave Pariente, Iacopo Poli, Giuseppe Luca Tommasone

Proceedings of the IEEE Hot Chips 33 Symposium, 2021

2020

The dynamics of learning with feedback alignment.

Maria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt

CoRR, 2020

Reservoir Computing meets Recurrent Kernels and Structured Transforms.

Jonathan Dong, Ruben Ohana, Mushegh Rafayelyan, Florent Krzakala

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

Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units.

Ruben Ohana, Jonas Wacker, Jonathan Dong, Sébastien Marmin, Florent Krzakala, Maurizio Filippone, Laurent Daudet

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020