Area of research
Artificial Intelligence · Statistical and Nonlinear Physics
Research interest
Research interests include Computer science, Inference, Large Hadron Collider, Particle physics, Machine learning, and Artificial intelligence.
Toward Machine Learning Optimization of Experimental Design
Mining gold from implicit models to improve likelihood-free inference
The frontier of simulation-based inference
Effective LHC measurements with matrix elements and machine learning
Mining for Dark Matter Substructure: Inferring Subhalo Population Properties from Strong Lenses with Machine Learning
Robust EEG-based cross-site and cross-protocol classification of states of consciousness
Machine Learning in High Energy Physics Community White Paper
Constraining Effective Field Theories with Machine Learning
A guide to constraining effective field theories with machine learning
API design for machine learning software: experiences from the scikit-learn project
arXiv (Cornell University) 2013cited by 1,801position: middle