563 citations · 717 across the 11 of their papers we have counts for
5 papers · 1 filter
A Mechanistic Study of Tabular Foundation Models
Marin Biloš, James T. Wilson, Anderson Schneider +1
Tabular foundation models with different architectures converge in accuracy across a range of classification and regression tasks. This raises questions a leaderboard cannot answer…
Quantile-Coupled Flow Matching for Distributional Reinforcement Learning
Michael Groom, Victor-Alexandru Darvariu, Lars Kunze +2
Unlike standard expected-return Reinforcement Learning (RL), Distributional RL (DRL) models the full return distribution, making it better-suited for uncertainty-aware and risk-sen…
AlphaLab: Autonomous Multi-Agent Research Across Optimization Domains with Frontier LLMs
Brendan R. Hogan, Xiwen Chen, James T. Wilson +5
We present AlphaLab, an autonomous research harness that leverages frontier LLM agentic capabilities to automate the full experimental cycle in quantitative, computation-intensive…
Compressing Convolutional Neural Networks
Wenlin Chen, James T. Wilson, Stephen Tyree +2
Convolutional neural networks (CNN) are increasingly used in many areas of computer vision. They are particularly attractive because of their ability to "absorb" great quantities o…
Compressing Neural Networks with the Hashing Trick
Wenlin Chen, James T. Wilson, Stephen Tyree +2
As deep nets are increasingly used in applications suited for mobile devices, a fundamental dilemma becomes apparent: the trend in deep learning is to grow models to absorb ever-in…