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Pascal Frossard

3 papers indexed

arxivcs.LG2026-07-21

DBMol: Design of High-Affinity, Target-Specific Small Molecules through Structure Prediction Models

Yiming Qin, Kai Yi, Miruna Cretu, Sjors H. W. Scheres, Pietro Liò, Pascal Frossard

Designing small molecule ligands that bind with high affinity to specific protein pockets is a fundamental goal in drug discovery, as small molecules constitute a major fraction of approved therapeutics. Recent breakthroughs in structure prediction, such as AlphaFold-3 and Boltz-…

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arxivstat.MLcs.AIcs.LG2026-07-08

DiPhon: Diffusion on Graphons for Scalable Graph Generation

Sergio Rozada, Yiming Qin, Manuel Madeira, Pascal Frossard, Alejandro Ribeiro

Diffusion models represent a leading paradigm for graph generation, with notable impact in domains such as molecular design. Yet, scaling these models to large graphs remains an open problem. We approach this question in the dense-graph setting through the lens of graphons, the s…

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arxivcs.CV2026-06-29

Uncertainty Estimation in Pathology Foundation Models via Deep Mutual Learning

Gbègninougbo Aurel Davy Tchokponhoue, Sevda Öğüt, Ali Idri, Dorina Thanou, Pascal Frossard

Pathology foundation models (PFMs) offer generalizable representations for whole-slide image (WSI) analysis, yet their clinical adoption remains limited. Specifically, their predictions lack reliable confidence estimates, and no single PFM is universally best across tasks, which…

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