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Machine Learning for Physics

Introduction to Data Science
Probability Theory and Density Estimation
Bayesian Statistics I
Bayesian Statistics II
Introduction to Artificial Intelligence and Machine Learning
Deep Learning and Generative Modeling
Convolutional and Recurrent Neural Networks
Project 01
Geometric Deep Learning and Graph Neural Networks
- Slides
- Geometric Deep Learning and Graph Neural Networks
Attention Mechanism and Transformers
- Slides
- Attention Mechanism and Transformers
Reinforcement Learning
AI Explainablility and Uncertainty Quantification
Unsupervised Learning and Anomaly Detection
- Slides
- Unsupervised Learning and Anomaly Detection
Physics Informed Neural Networks
Project 02
Learning from the Machines
- Slides
- Learning Physics from the Machines
Future of AI and Physics: What Lies Ahead?
- Slides
- Future of AI and Physics: What Lies Ahead?

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Project 01

Contents

Select from one of the following projects:

Project 01#

Select from one of the following projects:#

Higgs Boson Decaying to Tau Leptons
Searching for Exotic Particles
Galaxy Zoo
Nuclear Geometry and Characterization of the Quark Gluon Plasma
Dark Energy Survey
Aberrated Image Recovery of Ultracold Atoms

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Homework 06: Forecasting Projectile Motion with Recurrent Neural Networks

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Higgs Boson Decaying to Tau Leptons

Contents

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By Mark Neubauer

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