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Yulia Gusak
- Chargé de Recherches
- INRIA
- Department
- SATANAS
- Team
- Tools and Optimization for high Performance Applications and Learning
- E-mail address
- yulia.gusak
labri.fr - Tel
- +33 (0)9 99 99 99 99
Excerpt from publications
- Víctor Lucas Rosada Canesin, Julia Gusak. WiSP-OSch: Solver Within-Step Parallelism and Order Scheduling for Diffusion Sampling. ICLR 2026 - 2nd Workshop on Deep Generative Model in Machine Learning: Theory, Principle and Efficacy - Fourteenth International Conference on Learning Representation, Apr 2026, Rio De Janeiro, Brazil.
- Adrien Aguila--Multner, Olivier Beaumont, Lionel Eyraud-Dubois, Julia Gusak. Mind Bubbles and Memory: Bounds on Scheduling Pipeline Parallelism with Rematerialization. 2025.
- Adrien Aguila--Multner, Olivier Beaumont, Lionel Eyraud-Dubois, Julia Gusak. Optimized Forward-Backward Rematerialization for Memory-Efficient Pipeline Parallel Training. 2025.
- Julia Gusak, Xunyi Zhao, Théotime Le Hellard, Zhe Li, Lionel Eyraud-Dubois, et al.. HiRemate: Hierarchical Approach for Efficient Re-materialization of Large Neural Networks. Forty-Second International Conference on Machine Learning (ICML 2025), Jul 2025, Vancouver, Canada.
- Xunyi Zhao, Lionel Eyraud-Dubois, Théotime Le Hellard, Julia Gusak, Olivier Beaumont. OFFMATE: full fine-tuning of LLMs on a single GPU by re-materialization and offloading. 2024.