2 citations · 6 across the 16 of their papers we have counts for
5 papers · 1 filter
CyclOT: Learning Quadratic Optimal Transport Maps via Synchronized Forward-Backward Interpolants
Shizhou Xu, Jiachen Liu, Shih-Hsin Wang +4
We study the recovery of forward and reverse quadratic optimal-transport maps from unpaired samples in high dimensions. We introduce a bidirectional neural framework in which the l…
Observation geometry for uncertainty-aware Hamiltonian inference and experimental design in quantum magnets
Roy Liu, Venugopal Ranganathan, David Dahlbom +12
Determining microscopic interactions from spectroscopic and scattering measurements is central to understanding quantum materials, yet it often remains unclear which interactions c…
Mathematics of Data Science
Afonso S. Bandeira, Amit Singer, Thomas Strohmer
This book is about the mathematical foundations of data science. 1. Introduction 2. Curses, Blessings, and Surprises in High Dimensions 3. Singular Value Decomposition and Principa…
The "I Don't Know" Filter: Enhancing Agentic Reliability in Function Calling
Stefan Broecker, Mason del Rosario, Boris Selitser +1
The language models that underpin agents have seen a rapid rise in performance on function calling benchmarks. However, the metrics used in the training and evaluation of these mod…
Towards Multiscale Graph-based Protein Learning with Geometric Secondary Structural Motifs
Shih-Hsin Wang, Yuhao Huang, Taos Transue +4
Graph neural networks (GNNs) have emerged as powerful tools for learning protein structures by capturing spatial relationships at the residue level. However, existing GNN-based met…