Neural Simulation-based Inference - Lecture 5
Offered By: International Centre for Theoretical Sciences via YouTube
Course Description
Overview
Explore neural simulation-based inference techniques in this comprehensive lecture, part of the "Statistical Methods and Machine Learning in High Energy Physics" program. Delve into advanced topics presented by experts Elham E Khoda and Aishik Ghosh from the International Centre for Theoretical Sciences. Gain insights into the application of deep machine learning in high energy physics research, particularly in analyzing large datasets from experiments like the Large Hadron Collider. Learn about classification, identification, characterization, and estimation strategies used in searches for new physics. Benefit from this lecture's contribution to human resources development and capacity building in deep machine learning and artificial intelligence frameworks for high energy physics.
Syllabus
Neural Simulation-based Inference (Lecture 5) by Elham E Khoda & Aishik Ghosh
Taught by
International Centre for Theoretical Sciences
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent