MLO-lab / Uncertainty_Estimates_via_BVDLinks
The official source code to: Uncertainty Estimates of Predictions via a General Bias-Variance Decomposition (AISTATS'23)
☆11Updated 2 years ago
Alternatives and similar repositories for Uncertainty_Estimates_via_BVD
Users that are interested in Uncertainty_Estimates_via_BVD are comparing it to the libraries listed below
Sorting:
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Kernel Identification Through Transformers☆13Updated 2 years ago
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆30Updated last year
- ☆20Updated 3 years ago
- Repo for the Tutorials of Day1-Day2 of the Nordic Probabilistic AI School 2023☆17Updated 2 years ago
- Multi-Fidelity Active Learning with GFlowNets☆7Updated last year
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- Bayesian optimization with conformal coverage guarantees☆28Updated 2 years ago
- A repository for reproducing the results in Selection by Prediction paper☆15Updated 2 years ago
- Python package for Stein Thinning☆13Updated 7 months ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".☆53Updated 5 months ago
- Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"☆11Updated last year
- Python wrapper for the DPMMSubClusterStreaming.jl Julia package.☆14Updated 2 years ago
- This repository contains PyTorch implementations of various random feature maps for dot product kernels.☆21Updated 11 months ago
- Welcome to Uncertainty Metrics! The goal of this library is to provide an easy-to-use interface for both measuring uncertainty across Goo…☆24Updated 4 years ago
- A library for uncertainty quantification based on PyTorch☆121Updated 3 years ago
- Modular Gaussian Processes☆15Updated 3 years ago
- Codebase accompanying the paper "Diagnosing and Fixing Manifold Overfitting in Deep Generative Models"☆9Updated 10 months ago
- beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022☆44Updated 3 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 4 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated last year
- A Metropolis-Hastings MCMC sampler accelerated via diffusion models☆13Updated 11 months ago
- Code for "A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences"☆11Updated 4 months ago
- Efficient non-linear PCA through kernel PCA with the Nyström method☆13Updated 2 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆36Updated 3 years ago
- ☆31Updated 2 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 11 months ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆53Updated last year
- ☆22Updated last year