304 citations · 1.6k across the 183 of their papers we have counts for
192 papers
SeqMaestro: From nucleotide sequences to biological hypotheses through interpretable machine learning
Evgeny S. Saveliev, Krzysztof Kacprzyk, Charlotte Capitanchik +7
Nucleotide sequence analysis is central to problems spanning regulatory genomics, evolutionary biology, and phenotype prediction. Classical bioinformatics methods extract interpret…
Recursive Scaling in Masked Diffusion Models
Alba Carballo-Castro, Julianna Piskorz, Paulius Rauba +2
Masked diffusion models (MDMs) generate sequences by iteratively refining a partially masked state and committing tokens in parallel. We introduce recursion in MDMs and propose new…
Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces
Nicolás Astorga, Nabeel Seedat, Mihaela van der Schaar
Verifiable reward training has improved mathematical and coding reasoning, but these domains capture only part of step-by-step decision making. Many real-world tasks require findin…
Fast Generalization after Interpolation via Critically Damped Momentum Optimization
Luca Muscarnera, Silas Ruhrberg Estévez, Yuanzhang Xiao +1
A central problem in machine learning is that models can achieve near-perfect training performance while generalizing substantially less well to unseen examples. This gap is especi…
CellBRIDGE: Learning Cellular Trajectories via Interaction-Aware Alignment
Silas Ruhrberg Estévez, Nicolas Huynh, Tennison Liu +4
Inferring dynamics from population snapshots is a fundamental challenge in machine learning and biology. In scRNA-sequencing (scRNA-seq), destructive measurements preclude direct t…
Active Timepoint Selection for Learning Measure-Valued Trajectories
Nicolas Huynh, Mihaela van der Schaar
Inferring continuous probability paths from sparse snapshots is a fundamental challenge in domains like single-cell biology, where high-fidelity data acquisition is often destructi…