2 citations · 2 across the 3 of their papers we have counts for
4 papers
Self-Supervised Learning of Local Predictive Directions as a Neural Computation
Marco Zenari, Xuehao Ding, Daniel Burnham +3
Natural sensory dynamics are globally nonlinear but often exhibit simple local geometry, with nearby trajectories evolving preferentially along a small number of predictive directi…
Energy-Aware Routing to Large Reasoning Models
Austin R. Ellis-Mohr, Max Hartman, Lav R. Varshney
Large reasoning models (LRMs) have heterogeneous inference energy costs based on which model is used and how much it reasons. To reduce energy, it is important to choose the right…
Foundation Models for Discovery and Exploration in Chemical Space
Alexius Wadell, Anoushka Bhutani, Victor Azumah +26
Accurate prediction of atomistic, thermodynamic, and kinetic properties from molecular structures underpins materials innovation. Existing computational and experimental approaches…
A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search
Austin R. Ellis-Mohr, Anuj K. Nayak, Lav R. Varshney
Large language models (LLMs) demand considerable computational, energy, and financial resources during both training and deployment. While scaling laws for training have guided muc…