hakeemtonalli / deep-kernel-learningLinks
Implementation of deep kernels in GPyTorch and Pyro
☆12Updated 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:
- Bayesian Neural Network Surrogates for Bayesian Optimization☆63Updated last year
- Implementation of normalizing flows from 1d to Nd☆36Updated 4 years ago
- ☆10Updated 2 years ago
- Code for "A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences"☆15Updated 8 months ago
- Repository for 'Interpretable embeddings from molecular simulations using gaussian mixture variational autoencoders'☆20Updated 5 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆16Updated 2 years ago
- ☆155Updated 3 years ago
- ☆29Updated 3 years ago
- Bayesian Optimisation over Multiple Continuous and Categorical Inputs (CoCaBO)☆51Updated 6 years ago
- Heteroscedastic Bayesian Optimisation in Numpy☆23Updated 2 years ago
- A hello world Bayesian Neural Network project on MNIST☆48Updated 3 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆35Updated 2 months ago
- SAASBO: a package for high-dimensional bayesian optimization☆49Updated 4 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 5 months ago
- Regression datasets from the UCI repository with standardized test-train splits.☆48Updated 3 years ago
- Spectral-normalized Neural Gaussian Process (SNGP) implementation in PyTorch☆11Updated 3 years ago
- An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)☆42Updated 3 years ago
- Code for "Robust Multi-Objective Bayesian Optimization Under Input Noise"☆56Updated 3 years ago
- Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"☆77Updated 2 years ago
- Uncertainty quantification of molecular property prediction using Bayesian deep learning☆45Updated 6 years ago
- Bayesian optimization with conformal coverage guarantees☆28Updated 3 years ago
- Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model☆102Updated last year
- Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces☆64Updated 3 years ago
- Deep Bayesian Optimization for Problems with High-Dimensional Structure☆16Updated 3 years ago
- Stochastic Gradient Hamiltonian Monte Carlo☆12Updated 6 years ago
- Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".☆53Updated this week
- Official Implementation of "Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning"☆15Updated 2 years ago
- Implementation of the Latent CCM paper☆16Updated last year