Roger Grosse Optimizing Neural Networks Using Structured Probabilistic Models

May 25, 2026
Topic Brief: Introduction to Machine Learning (CSC2515 - Fall 2021), Department of Computer Science, University of Toronto.

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  • Introduction to Machine Learning (CSC2515 - Fall 2021), Department of Computer Science, University of Toronto.

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Roger Grosse: Optimizing neural networks using structured probabilistic models

Roger Grosse: Optimizing neural networks using structured probabilistic models

Read more details and related context about Roger Grosse: Optimizing neural networks using structured probabilistic models.

Evaluating Lossy Compression Rates of Deep Generative Models - Roger Grosse

Evaluating Lossy Compression Rates of Deep Generative Models - Roger Grosse

Read more details and related context about Evaluating Lossy Compression Rates of Deep Generative Models - Roger Grosse.

The Brains Behind AI: Roger Grosse

The Brains Behind AI: Roger Grosse

Read more details and related context about The Brains Behind AI: Roger Grosse.

LESSON 14: DEEP LEARNING MATHEMATICS: Understanding Structured Probability Model

LESSON 14: DEEP LEARNING MATHEMATICS: Understanding Structured Probability Model

Read more details and related context about LESSON 14: DEEP LEARNING MATHEMATICS: Understanding Structured Probability Model.

Self-Tuning Networks: Amortizing the Hypergradient Computation for Hyperparameter Optimization

Self-Tuning Networks: Amortizing the Hypergradient Computation for Hyperparameter Optimization

Read more details and related context about Self-Tuning Networks: Amortizing the Hypergradient Computation for Hyperparameter Optimization.

DLRLSS 2019 - Bayesian Deep Learning - Roger Grosse

DLRLSS 2019 - Bayesian Deep Learning - Roger Grosse

Read more details and related context about DLRLSS 2019 - Bayesian Deep Learning - Roger Grosse.

Structured Probabilistic Models in Deep Learning

Structured Probabilistic Models in Deep Learning

Deep learning is useful to do much more than classification. Most importantly it can be used to

Probabilistic ML — Lecture 25 — Customizing Probabilistic Models & Algorithms

Probabilistic ML — Lecture 25 — Customizing Probabilistic Models & Algorithms

Read more details and related context about Probabilistic ML — Lecture 25 — Customizing Probabilistic Models & Algorithms.

Introduction to ML - Lecture 7 - Probabilistic Models (Part 1)

Introduction to ML - Lecture 7 - Probabilistic Models (Part 1)

Introduction to Machine Learning (CSC2515 - Fall 2021), Department of Computer Science, University of Toronto. Lecture 07: ...

UW CSE Colloquia: Roger Grosse (MIT)

UW CSE Colloquia: Roger Grosse (MIT)

Read more details and related context about UW CSE Colloquia: Roger Grosse (MIT).