Skip to content
Lecture notes on Bayesian deep learning
Branch: master
Clone or download
Latest commit 8848698 Feb 11, 2018
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
1_elementary_mathematics.pdf
2_gaussian_process.pdf Add files via upload Feb 8, 2018
3_bayesian_deep_learning.pdf Add files via upload Feb 9, 2018
4_summary.pdf Add files via upload Feb 9, 2018
5_uncertainty-in-deep-learning.pdf Add files via upload Feb 9, 2018
README.md Update README.md Feb 11, 2018

README.md

Understanding Bayesian Deep Learning

1. Elementary mathematics

  • Set theory
  • Measure theory
  • Probability
  • Random variable
  • Random process
  • Functional analysis (harmonic analysis)

2. Gaussian process

  • Gaussian process
  • Weight-space view
  • Function-space view
  • Gaussian process latent variable model

3. Bayesian neural netwrok

  • Minimum description length
  • Ensemble learning in Bayesian neural network
  • Practical variational inference
  • Bayes by backprop
  • Summary of variational inference
  • Dropout as a Bayesian approximation
  • Stein variational gradient descent

4. Summary

  • Measure thoery
  • Probability
  • Random variable
  • Random process
  • Gaussian process
  • Functional Analysis
  • Summary of variational inference
  • Stein variational gradient descent

5. Uncertainty in Deep Learning

  • Yarin Gal, Uncertainty in Deep Learning
  • Anonymous, Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
  • Patrick McClure, Representing Inferential Uncertainty in Deep Neural Networks through Sampling
  • Balaji Lakshminarayanan, Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
  • Alex Kendal, What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
  • Gregory Kahn, Uncertainty-Aware Reinforcement Learning for Collision Avoidance
  • Charles Richter, Safe Visual Navigation via Deep Learning and Novelty Detection
  • Sungjoon Choi, Uncertainty-Aware Learning from Demonstration Using Mixture Density Networks with Sampling-Free Variance Modeling
You can’t perform that action at this time.