10 papers
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…
Machine Unlearning via Information Theoretic Regularization
Shizhou Xu, Thomas Strohmer
How can we effectively remove or ``unlearn'' undesirable information, such as specific features or the influence of individual data points, from a learning outcome while minimizing…
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…
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)
Andrew Ferguson, Marisa LaFleur, Lars Ruthotto +97
This community paper developed out of the NSF Workshop on the Future of Artificial Intelligence (AI) and the Mathematical and Physics Sciences (MPS), which was held in March 2025 w…
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…