zhulingchen / tfp-tutorial
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
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 5 years ago
- ☆28Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- Implementation of (2018) Neural Ordinary Differential Equations on Keras☆64Updated 5 years ago
- Pytorch implementation of Recurrent Neural Processes https://arxiv.org/pdf/1906.05915.pdf☆21Updated 5 years ago
- Modeling Uncertainty in RNNs for Time Series Forecasting☆14Updated 7 years ago
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆38Updated 2 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- Experiments with Neural Ordinary Differential Equations on image and text classification tasks☆31Updated 5 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- Python and MATLAB code for Stein Variational sampling methods☆24Updated 5 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆71Updated 2 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 3 years ago
- Parametric Gaussian Process Regression for Big Data☆44Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 8 months ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Implementations of normalizing flows using python and tensorflow☆24Updated 3 months ago
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- Code for "On the Expressiveness of Approximate Inference in Bayesian Neural Networks"☆13Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆88Updated 4 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- ☆28Updated 5 years ago
- Reproducing the results of the paper "Bayesian Recurrent Neural Networks" by Fortunato et al.☆40Updated 6 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 4 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆81Updated 4 years ago
- ☆30Updated 2 years ago
- Implementation of different Normalizing Flows, NF, Planar Flows, IAF, etc.☆27Updated 6 years ago