desi-ivanova / idad
Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
☆19Updated 3 years ago
Alternatives and similar repositories for idad:
Users that are interested in idad are comparing it to the libraries listed below
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆30Updated 3 years ago
- ☆15Updated 2 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆21Updated 4 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 3 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- ☆49Updated 2 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…☆14Updated 4 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆70Updated 4 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 8 months ago
- Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch☆15Updated 3 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated last year
- ☆53Updated 7 months ago
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆19Updated 2 years ago
- Bayesian active learning with EPIG data acquisition☆28Updated last month
- [NeurIPS'19] Deep Equilibrium Models Jax Implementation☆39Updated 4 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 7 months ago
- Code for Accelerated Linearized Laplace Approximation for Bayesian Deep Learning (ELLA, NeurIPS 22')☆16Updated 2 years ago
- Gaussian Processes for Sequential Data☆18Updated 4 years ago
- Code for our paper: Online Variational Filtering and Parameter Learning☆18Updated 3 years ago
- ☆80Updated 3 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago