3 citations · 3 across the 8 of their papers we have counts for
6 papers · 1 filter
Accelerating scientific discovery with the common task framework
J. Nathan Kutz, Peter Battaglia, Michael Brenner +12
Machine learning (ML) and artificial intelligence (AI) algorithms are transforming and empowering the characterization and control of dynamic systems in the engineering, physical,…
Meshless solutions of PDE inverse problems on irregular geometries
James V. Roggeveen, Michael P. Brenner
Solving inverse and optimization problems over solutions of nonlinear partial differential equations (PDEs) on complex spatial domains is a long-standing challenge. Here we introdu…
Learning constitutive models and rheology from partial flow measurements
Alp M. Sunol, James V. Roggeveen, Mohammed G. Alhashim +2
Constitutive laws relate fluid stress to deformation and underpin predictions of non-Newtonian behavior in industrial and biological fluids. Standard characterization relies on mea…
CMT-Benchmark: A Benchmark for Condensed Matter Theory Built by Expert Researchers
Haining Pan, James V. Roggeveen, Erez Berg +16
Large language models (LLMs) have shown remarkable progress in coding and math problem-solving, but evaluation on advanced research-level problems in hard sciences remains scarce.…
EEFSUVA: A New Mathematical Olympiad Benchmark
Nicole N Khatibi, Daniil A. Radamovich, Michael P. Brenner
Recent breakthroughs have spurred claims that large language models (LLMs) match gold medal Olympiad to graduate level proficiency on mathematics benchmarks. In this work, we exami…
HARDMath2: A Benchmark for Applied Mathematics Built by Students as Part of a Graduate Class
James V. Roggeveen, Erik Y. Wang, Will Flintoft +42
Large language models (LLMs) have shown remarkable progress in mathematical problem-solving, but evaluation has largely focused on problems that have exact analytical solutions or…