Publications (7)
Mapping Network States Using Connectivity Queries
Alexander RodrÃguez, Bijaya Adhikari, Andrés D. González +3
Can we infer all the failed components of an infrastructure network, given a sample of reachable nodes from supply nodes? One of the most critical post-disruption processes after a…
Objective Scaling Ensemble Approach for Integer Linear Programming
Weili Zhang, Charles Nicholson
The objective scaling ensemble approach is a novel two-phase heuristic for integer linear programming problems shown to be effective on a wide variety of integer linear programming…
Improving Heart-Focused Medical Question Answering in LLMs via Variance-Aware Rubric Rewards with GRPO
Arash Ahmadi, Parisa Masnadi, Parisa Masnadi Khiabani +4
Large Language Models (LLMs) have shown strong promise in healthcare applications. Yet deploying general-purpose models in real-world settings remains difficult due to data privacy…
PlumeQuant: Uncertainty-aware consistency assessment of methane plume masks and emission-rate estimates
Parisa Masnadi Khiabani, Wolfgang Jentner, Alireza Rangrazjeddi +4
The paper presents PlumeQuant, a framework that quantifies uncertainty and consistency of methane plume masks and derived emission rates by generating alternative plausible masks w…
TensorFlow.js: Machine Learning for the Web and Beyond
Daniel Smilkov, Nikhil Thorat, Yannick Assogba +17
TensorFlow.js is a library for building and executing machine learning algorithms in JavaScript. TensorFlow.js models run in a web browser and in the Node.js environment. The libra…
Embedding Projector: Interactive Visualization and Interpretation of Embeddings
Daniel Smilkov, Nikhil Thorat, Charles Nicholson +3
Embeddings are ubiquitous in machine learning, appearing in recommender systems, NLP, and many other applications. Researchers and developers often need to explore the properties o…
Discovery of Nonlinear Dynamics with Automated Basis Function Generation
Mohammad Amin Basiri, Charles Nicholson
Discovering governing equations from observational data remains a fundamental challenge in scientific modeling, particularly when the underlying mathematical structure is unknown.…