PrincetonLIPS / AHGPLinks
[NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
☆23Updated 4 years ago
Alternatives and similar repositories for AHGP
Users that are interested in AHGP are comparing it to the libraries listed below
Sorting:
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆20Updated 3 years ago
- ☆51Updated 2 years ago
- ☆15Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Normalizing Flows using JAX☆84Updated last year
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆40Updated 2 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- Implementation of Action Matching for the Schrödinger equation☆24Updated 2 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- Stochastic Normalizing Flows☆78Updated 3 years ago
- Bayesian algorithm execution (BAX)☆50Updated 4 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling☆36Updated 3 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Library for normalizing flows and neural flows.☆25Updated 3 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆18Updated 5 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 4 months ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 7 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Bayesian Optimization with Density-Ratio Estimation☆24Updated 2 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆37Updated 4 years ago
- Pre-trained Gaussian processes for Bayesian optimization☆97Updated 5 months ago
- Kernel Identification Through Transformers☆14Updated 2 years ago