Jean-Christophe Gagnon-Audet

According to our database, Jean-Christophe Gagnon-Audet authored at least 16 papers between 2021 and 2026.

Collaborative distances:

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

2026

AIRA_2: Overcoming Bottlenecks in AI Research Agents.

Karen Hambardzumyan, Nicolas Mario Baldwin, Edan Toledo, Rishi Hazra, Michael Kuchnik, Bassel Al Omari, Thomas Foster, Anton Protopopov, Jean-Christophe Gagnon-Audet, Ishita Mediratta, Kelvin Niu, Michael Shvartsman, Alisia Maria Lupidi, Alexis Audran-Reiss, Parth Pathak, Tatiana Shavrina, Despoina Magka, Hela Momand, Derek Dunfield, Nicola Cancedda, Pontus Stenetorp, Carole-Jean Wu, Jakob Nicolaus Foerster, Yoram Bachrach, Martin Josifoski

CoRR, March, 2026

AIRS-Bench: a Suite of Tasks for Frontier AI Research Science Agents.

Alisia Maria Lupidi, Bhavul Gauri, Thomas Foster, Bassel Al Omari, Despoina Magka, Alberto Pepe, Alexis Audran-Reiss, Muna Aghamelu, Nicolas Mario Baldwin, Lucia Cipolina-Kun, Jean-Christophe Gagnon-Audet, Chee Hau Leow, Sandra Lefdal, Hossam Mossalam, Abhinav Moudgil, Saba Nazir, Emanuel Tewolde, Isabel Urrego, Jordi Armengol-Estapé, Amar Budhiraja, Gaurav Chaurasia, Abhishek Charnalia, Derek Dunfield, Karen Hambardzumyan, Daniel Izcovich, Martin Josifoski, Ishita Mediratta, Kelvin Niu, Parth Pathak, Michael Shvartsman, Edan Toledo, Anton Protopopov, Roberta Raileanu, Alexander H. Miller, Tatiana Shavrina, Jakob N. Foerster, Yoram Bachrach

CoRR, February, 2026

A Scalable Measure of Loss Landscape Curvature for Analyzing the Training Dynamics of LLMs.

Dayal Singh Kalra, Jean-Christophe Gagnon-Audet, Andrey Gromov, Ishita Mediratta, Kelvin Niu, Alexander H. Miller, Michael Shvartsman

CoRR, January, 2026

2025

What Does It Take to Be a Good AI Research Agent? Studying the Role of Ideation Diversity.

Alexis Audran-Reiss, Jordi Armengol-Estapé, Karen Hambardzumyan, Amar Budhiraja, Martin Josifoski, Edan Toledo, Rishi Hazra, Despoina Magka, Michael Shvartsman, Parth Pathak, Justine T. Kao, Lucia Cipolina-Kun, Bhavul Gauri, Jean-Christophe Gagnon-Audet, Emanuel Tewolde, Jenny Zhang, Taco Cohen, Yossi Adi, Tatiana Shavrina, Yoram Bachrach

CoRR, November, 2025

AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench.

Edan Toledo, Karen Hambardzumyan, Martin Josifoski, Rishi Hazra, Nicolas Mario Baldwin, Alexis Audran-Reiss, Michael Kuchnik, Despoina Magka, Minqi Jiang, Alisia Maria Lupidi, Andrei Lupu, Roberta Raileanu, Kelvin Niu, Tatiana Shavrina, Jean-Christophe Gagnon-Audet, Michael Shvartsman, Shagun Sodhani, Alexander H. Miller, Abhishek Charnalia, Derek Dunfield, Carole-Jean Wu, Pontus Stenetorp, Nicola Cancedda, Jakob Nicolaus Foerster, Yoram Bachrach

CoRR, July, 2025

The Automated LLM Speedrunning Benchmark: Reproducing NanoGPT Improvements.

Bingchen Zhao, Despoina Magka, Minqi Jiang, Xian Li, Roberta Raileanu, Tatiana Shavrina, Jean-Christophe Gagnon-Audet, Kelvin Niu, Shagun Sodhani, Michael Shvartsman, Andrei Lupu, Alisia Maria Lupidi, Edan Toledo, Karen Hambardzumyan, Martin Josifoski, Thomas Foster, Lucia Cipolina-Kun, Abhishek Charnalia, Derek Dunfield, Alexander H. Miller, Oisin Mac Aodha, Jakob N. Foerster, Yoram Bachrach

CoRR, June, 2025

Scaling and Distilling Transformer Models for sEMG.

Nicholas Mehlman, Jean-Christophe Gagnon-Audet, Michael Shvartsman, Kelvin Niu, Alexander H. Miller, Shagun Sodhani

Trans. Mach. Learn. Res., 2025

2024

Effective Latent Differential Equation Models via Attention and Multiple Shooting.

Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Pablo Polosecki, Irina Rish, Silvina Ponce Dawson, Guillermo A. Cecchi, Guillaume Dumas

Trans. Mach. Learn. Res., 2024

2023

WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series.

Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad-Javad Darvishi Bayazi, Pooneh Mousavi, Guillaume Dumas, Irina Rish

Trans. Mach. Learn. Res., 2023

GOKU-UI: Ubiquitous Inference through Attention and Multiple Shooting for Continuous-time Generative Models.

Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Irina Rish, Pablo Polosecki, Silvina Ponce Dawson, Guillermo A. Cecchi, Guillaume Dumas

CoRR, 2023

2022

Generative Models of Brain Dynamics.

Mahta Ramezanian-Panahi, Germán Abrevaya, Jean-Christophe Gagnon-Audet, Vikram Voleti, Irina Rish, Guillaume Dumas

Frontiers Artif. Intell., 2022

WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series Tasks.

Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad-Javad Darvishi Bayazi, Guillaume Dumas, Irina Rish

CoRR, 2022

A Remedy For Distributional Shifts Through Expected Domain Translation.

Jean-Christophe Gagnon-Audet, Soroosh Shahtalebi, Frank Rudzicz, Irina Rish

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks.

Germán Abrevaya, Guillaume Dumas, Aleksandr Y. Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James R. Kozloski, Pablo Polosecki, Guillaume Lajoie, David D. Cox, Silvina Ponce Dawson, Guillermo A. Cecchi, Irina Rish

Neural Comput., 2021

SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization.

Soroosh Shahtalebi, Jean-Christophe Gagnon-Audet, Touraj Laleh, Mojtaba Faramarzi, Kartik Ahuja, Irina Rish

CoRR, 2021

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization.

Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish

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