rmgarnett / cse515t
Materials for Bayesian Methods in Machine Learning Course
☆88Updated 5 months ago
Alternatives and similar repositories for cse515t:
Users that are interested in cse515t are comparing it to the libraries listed below
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- ☆77Updated 8 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆66Updated 7 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆182Updated 6 years ago
- Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18☆66Updated 6 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 8 years ago
- I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth☆184Updated 10 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆120Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Convolutional Gaussian processes based on GPflow.☆96Updated 7 years ago
- Deep exponential families (DEFs)☆55Updated 7 years ago
- A Python library for reinforcement learning using Bayesian approaches☆54Updated 9 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆105Updated 7 years ago
- Variational Fourier Features☆84Updated 3 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Edward content including papers, posters, and talks☆91Updated 4 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆31Updated 5 years ago
- Black box variational inference for state space models☆1Updated 8 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)☆42Updated 5 years ago
- Open access book on variational Bayesian methods written collaboratively☆28Updated 10 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- ☆40Updated 6 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 6 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- Notebooks explaining the intuition behind the Expectation Maximisation algorithm☆39Updated 6 years ago