3 citations · 6 across the 11 of their papers we have counts for
4 papers · 1 filter
SLEM: Spectrum-Aware Latent Expert Merging
Dohyeon Kim, Bedionita Soro, Bruno Andreis +1
Mixture-of-Experts (MoE) models scale model capacity efficiently by activating only a small subset of experts for each input, while still requiring all parameters to be stored in m…
MotionJEPA: Preventing Temporal Feature Collapse by Capturing Visual Changes in Latent Space
Markus Karmann, Shile Li, Christian Internò +10
Joint Embedding Predictive Architectures (JEPAs) are a promising paradigm for learning task-agnostic latent world models without visual reconstruction. However, standard JEPA train…
Procedural Pretraining for Molecular Property Prediction
Moritz Friedemann, Zachary Shinnick, Philip Torr +1
Molecular property prediction is often limited by the small size of labeled downstream datasets, motivating pretraining on large corpora of unlabeled molecules. In this work, we as…
Online Surrogate Repair: Decoupling High-Fidelity Feedback from Search Length in Closed-Loop Discovery
Xiaotang Feng, Philip Torr, Bruno Andreis
Closed-loop AI scientists can generate candidate designs at low marginal computational cost, whereas reliable feedback may require wet-lab synthesis, characterization, or high-fide…