hakeemtonalli / deep-kernel-learningLinks
Implementation of deep kernels in GPyTorch and Pyro
☆10Updated 4 years ago
Alternatives and similar repositories for deep-kernel-learning
Users that are interested in deep-kernel-learning are comparing it to the libraries listed below
Sorting:
- ☆10Updated last year
- Spectral-normalized Neural Gaussian Process (SNGP) implementation in PyTorch☆9Updated 3 years ago
- Implementation of normalizing flows from 1d to Nd☆36Updated 4 years ago
- ☆23Updated 3 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆73Updated 3 years ago
- A hello world Bayesian Neural Network project on MNIST☆44Updated 3 years ago
- ☆14Updated 4 years ago
- ☆29Updated 2 years ago
- Repository for 'Interpretable embeddings from molecular simulations using gaussian mixture variational autoencoders'☆20Updated 5 years ago
- Regression datasets from the UCI repository with standardized test-train splits.☆47Updated 3 years ago
- GraphCON (ICML 2022)☆59Updated 2 years ago
- Implementation of the Latent CCM paper☆16Updated last year
- Neural Graph Differential Equations (Neural GDEs)☆204Updated 4 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆53Updated last year
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Bayesian optimization with conformal coverage guarantees☆28Updated 2 years ago
- TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155☆142Updated 2 years ago
- Official Implementation of "Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning"☆15Updated 2 years ago
- Bayesian neural networks via MCMC: tutorial☆57Updated 9 months ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆16Updated 2 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆61Updated 4 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Toy Examples of Conditional Density Estimation with Bayesian Normalizing flows☆22Updated 6 years ago
- Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'☆38Updated 6 years ago
- [ICLR2024] Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data☆47Updated 6 months ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆223Updated last year
- Various code/notebooks to benchmark different ways we could estimate uncertainty in ML predictions.☆42Updated 4 years ago
- Heteroscedastic Bayesian Optimisation in Numpy☆21Updated 2 years ago
- ☆151Updated 2 years ago
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆69Updated 5 years ago