Hugo Talibart

The paper presents an ensemble model that improves predictions of perceptual similarity between odor mixtures using a curated dataset and collaborative challenge results.

The paper introduces a Transformer-based VAE for molecular encoding and generation, achieving high reconstruction accuracy and a well-structured latent space aligned with chemical similarity.

This paper introduces StructureDCA, a method that improves mutational landscape predictions by integrating structural information into direct coupling analysis.

PPalign optimally aligns Potts models of proteins using integer linear programming, improving alignment of remotely related sequences compared to existing methods.

ComPotts aligns Potts models of proteins to improve pairwise sequence alignment by considering coevolutionary relationships.