4 papers
Knowledge-Informed Kernel State Reconstruction from Heterogeneous Partial Observations
Luca Muscarnera, Silas Ruhrberg Estévez, Samuel Holt +2
Real-world scientific systems are rarely observed through complete, regularly sampled state trajectories. Instead, measurements are often partial, noisy, and heterogeneous, providi…
Influence-Guided Symbolic Regression: Scientific Discovery via LLM-Driven Equation Search with Granular Feedback
Evgeny S. Saveliev, Samuel Holt, Nabeel Seedat +3
Large Language Models (LLMs) offer a promising avenue for scientific discovery, yet their application to symbolic regression is often constrained by inefficient search strategies a…
Towards Human-Guided, Data-Centric LLM Co-Pilots
Evgeny Saveliev, Jiashuo Liu, Nabeel Seedat +2
Machine learning (ML) has the potential to revolutionize various domains, but its adoption is often hindered by the disconnect between the needs of domain experts and translating t…
CliMB: An AI-enabled Partner for Clinical Predictive Modeling
Evgeny Saveliev, Tim Schubert, Thomas Pouplin +2
Despite its significant promise and continuous technical advances, real-world applications of artificial intelligence (AI) remain limited. We attribute this to the "domain expert-A…