Théotime Le Hellard

According to our database, Théotime Le Hellard authored at least 6 papers between 2023 and 2026.

Collaborative distances:

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

2026

Survival Reinforcement Learning: Toward Scalable Self-Supervised RL.

Franki Nguimatsia Tiofack, Fabian Schramm, Théotime Le Hellard, Justin Carpentier

CoRR, May, 2026

Accelerating trajectory optimization with Sobolev-trained diffusion policies.

Théotime Le Hellard, Franki Nguimatsia Tiofack, Quentin Le Lidec, Justin Carpentier

CoRR, April, 2026

SVL: Goal-Conditioned Reinforcement Learning as Survival Learning.

Franki Nguimatsia Tiofack, Fabian Schramm, Théotime Le Hellard, Justin Carpentier

CoRR, April, 2026

2025

Guided Flow Policy: Learning from High-Value Actions in Offline Reinforcement Learning.

Franki Nguimatsia Tiofack, Théotime Le Hellard, Fabian Schramm, Nicolas Perrin-Gilbert, Justin Carpentier

CoRR, December, 2025

HiRemate: Hierarchical Approach for Efficient Re-materialization of Neural Networks.

Julia Gusak, Xunyi Zhao, Théotime Le Hellard, Zhe Li, Lionel Eyraud-Dubois, Olivier Beaumont

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2023

Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch.

Xunyi Zhao, Théotime Le Hellard, Lionel Eyraud-Dubois, Julia Gusak, Olivier Beaumont

Proceedings of the International Conference on Machine Learning, 2023