zhulingchen / tfp-tutorialLinks
TensorFlow Probability Tutorial
☆37Updated 5 years ago
Alternatives and similar repositories for tfp-tutorial
Users that are interested in tfp-tutorial are comparing it to the libraries listed below
Sorting:
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- ☆28Updated 6 years ago
- Experiments with Neural Ordinary Differential Equations on image and text classification tasks☆31Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated last year
- Pytorch implementation of Recurrent Neural Processes https://arxiv.org/pdf/1906.05915.pdf☆22Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 5 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆38Updated 2 years ago
- Modeling Uncertainty in RNNs for Time Series Forecasting☆14Updated 7 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆72Updated 3 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021)☆118Updated 4 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Implementation of different Normalizing Flows, NF, Planar Flows, IAF, etc.☆28Updated 7 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆32Updated 3 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- Pytorch implementation for "Particle Flow Bayes' Rule"☆14Updated 6 years ago
- Bayesian calibration using Tensorflow Probability☆35Updated 6 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- Tensorflow 2.x implementation of the beta-TCVAE (arXiv:1802.04942).☆16Updated 5 years ago
- Pytorch implementation of Markov RNNs☆16Updated 6 years ago