Pascal Poupart

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This channel includes video lectures by Pascal Poupart, who is a professor in the David R. Cheriton School of Computer Science at the University of Waterloo ...

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CS885 Module 6 Inverse RL

CS885 Module 5 Distributional RL

CS885 Module 4 Partially Observable Reinforcement Learning

CS885 Module 3 Imitation Learning

CS885 Module 2 Maximum Entropy Reinforcement Learning

CS885 Module 1 Trust region & proximal policy optimization

CS480680 Lecture 24 Gradient boosting, bagging, decision forests

CS480680 Lecture 23 Normalizing flows (Priyank Jaini)

CS480680 Lecture 22 Ensemble learning (bagging and boosting)

CS480680 Lecture 21 Generative networks (variational autoencoders and GANs)

CS480680 Lecture 20 Autoencoders

CS480680 Lecture 19 Attention and Transformer Networks

CS480680 Lecture 18 Recurrent and recursive neural networks

CS480680 Lecture 17 Hidden Markov Models

CS480680 Lecture 16 Convolutional neural networks

CS480680 Lecture 15 Deep neural networks

CS480680 Lecture 14 Support vector machines (continued)

CS480680 Lecture 13 Support vector machines

CS480680 Lecture 12 Gaussian Processes

CS480680 Lecture 11 Kernel Methods

CS480680 Lecture 10 Multi-layer neural networks and backpropagation

CS480680 Lecture 9 Perceptrons and single layer neural nets

CS480680 Lecture 8 Logistic regression and generalized linear models

CS480680 Lecture 7 Mixture of Gaussians

CS480680 Lecture 6 Model compression for NLP (Ashutosh Adhikari)

CS480680 Lecture 6 EM and mixture models (Guojun Zhang)

CS480680 Lecture 6 Sum-product networks (Pranav Subramani)

CS480680 Lecture 6 Fact checking and reinforcement learning (Vik Goel)

CS480680 Lecture 6 Unsupervised word translation (Kira Selby)

CS480680 Lecture 6 Normalizing flows (Priyank Jaini)