PSI 2018/2019 - Machine Learning (Hayward Sierens)

PSI 2018/2019 - Machine Learning (Hayward Sierens)

 

Friday Apr 12, 2019
Speaker(s): 

Generative modelling: explicit and approximate likelihood models; implicit likelihood models

 

Thursday Apr 11, 2019
Speaker(s): 

Generative modelling: explicit and tractable likelihood models

 

Wednesday Apr 10, 2019
Speaker(s): 

Quantum state reconstruction using restricted Boltzmann machines

 

Tuesday Apr 09, 2019
Speaker(s): 

Restricted Boltzmann machines: training to minimize the Kullback-Liebler divergence

 

Monday Apr 08, 2019
Speaker(s): 

Generative modelling: Hopfield networks, Boltzmann machines and restricted Boltzmann machines (RBMs)

 

Friday Apr 05, 2019
Speaker(s): 

Reinforcement learning: Q-learning, Bellman equations

 

Thursday Apr 04, 2019
Speaker(s): 

Reinforcement learning: Markov decision processes, policy gradient methods

 

Wednesday Apr 03, 2019

Dimensional reduction using t-distributed stochastic neighbour embedding (t-SNE); Kullback-Liebler (KL) divergence; maximum likelihood estimation

 

Tuesday Apr 02, 2019

Introduction to unsupervised learning; dimensional reduction using principal component analysis

 

Monday Apr 01, 2019

Convolutional neural networks: local receptive fields, shared weights and biases, pooling

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