1 citations · 1 across the 2 of their papers we have counts for
3 papers
EvoFlows: Evolutionary Edit-Based Flow-Matching for Protein Engineering
Nicolas Deutschmann, Constance Ferragu, Jonathan D. Ziegler +2
We introduce EvoFlows, a variable-length protein sequence-to-sequence modeling approach designed for protein engineering. Existing protein language models are poorly suited for opt…
g-DPO: Scalable Preference Optimization for Protein Language Models
Constance Ferragu, Jonathan D. Ziegler, Nicolas Deutschmann +3
Direct Preference Optimization (DPO) is an effective approach for aligning protein language models with experimental design goals. However, DPO faces a scalability bottleneck: the…
Multimodal CLIP Inference for Meta-Few-Shot Image Classification
Constance Ferragu, Philomene Chagniot, Vincent Coyette
In recent literature, few-shot classification has predominantly been defined by the N-way k-shot meta-learning problem. Models designed for this purpose are usually trained to exce…