PSI 2018/2019 - Machine Learning (Hayward)
Organizer(s): Lauren Hayward
Collection URL: http://pirsa.org/C19011
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![]() | PSI 2018/2019 - Machine Learning - Lecture 1 Speaker(s): Lauren Hayward
Abstract:
Motivation; goals of machine learning and many-body physics; definitions of supervised, unsupervised and reinforcement learning Date: 25/03/2019 - 9:00 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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![]() | PSI 2018/2019 - Machine Learning - Lecture 2 Speaker(s): Lauren Hayward
Abstract:
Supervised learning with feedforward neural networks: weights and biases, activation functions, cost functions, gradient descent Date: 26/03/2019 - 9:00 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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![]() | PSI 2018/2019 - Machine Learning - Lecture 3 Speaker(s): Lauren Hayward
Abstract:
Alternatives to gradient descent, backpropagation, recognizing overfitting Date: 27/03/2019 - 9:00 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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![]() | PSI 2018/2019 - Machine Learning - Lecture 4 Speaker(s): Lauren Hayward
Abstract:
Training, validation and testing datasets; methods that prevent overfitting; using supervised neural networks to classify phases of matter (classical Ising model, classical Ising gauge theory) Date: 28/03/2019 - 9:00 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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![]() | PSI 2018/2019 - Machine Learning - Lecture 5 Speaker(s): Lauren Hayward
Abstract:
Monte Carlo sampling; summary of hyperparameters in feedforward neural networks Date: 29/03/2019 - 9:00 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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![]() | PSI 2018/2019 - Machine Learning - Lecture 6 Speaker(s): Lauren Hayward
Abstract:
Convolutional neural networks: local receptive fields, shared weights and biases, pooling Date: 01/04/2019 - 9:00 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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![]() | PSI 2018/2019 - Machine Learning - Lecture 7 Speaker(s): Lauren Hayward
Abstract:
Introduction to unsupervised learning; dimensional reduction using principal component analysis Date: 02/04/2019 - 9:00 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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![]() | PSI 2018/2019 - Machine Learning - Lecture 8 Speaker(s): Lauren Hayward
Abstract:
Dimensional reduction using t-distributed stochastic neighbour embedding (t-SNE); Kullback-Liebler (KL) divergence; maximum likelihood estimation Date: 03/04/2019 - 10:15 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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![]() | PSI 2018/2019 - Machine Learning - Lecture 9 Speaker(s): Bohdan Kulchytskyy
Abstract:
Reinforcement learning: Markov decision processes, policy gradient methods Date: 04/04/2019 - 9:00 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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![]() | PSI 2018/2019 - Machine Learning - Lecture 10 Speaker(s): Bohdan Kulchytskyy
Abstract:
Reinforcement learning: Q-learning, Bellman equations Date: 05/04/2019 - 9:00 am
Collection: PSI 2018/2019 - Machine Learning (Hayward)
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