fKunstner / dataset-downloaderLinks
☆13Updated last year
Alternatives and similar repositories for dataset-downloader
Users that are interested in dataset-downloader are comparing it to the libraries listed below
Sorting:
- A community repository for benchmarking Bayesian methods☆111Updated 3 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆100Updated 6 years ago
- Bayesian active learning with EPIG data acquisition☆34Updated 2 months ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- ☆155Updated 3 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Evaluating variational inference using Pareto-smoothed importance sampling and simulation-based calibration☆12Updated 7 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Regression datasets from the UCI repository with standardized test-train splits.☆48Updated 3 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆20Updated 3 years ago
- ☆24Updated 4 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆16Updated 2 years ago
- Random Fourier Features☆50Updated 8 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆108Updated last year
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 5 years ago
- Fair Empirical Risk Minimization (FERM)☆37Updated 5 years ago
- Testing methods for estimating KL-divergence from samples.☆68Updated 7 months ago
- Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille☆91Updated 8 months ago
- Density Ratio Estimation via Infinitesimal Classification (AISTATS 2022 Oral)☆20Updated 3 years ago
- [NeurIPS DBT 2021] HPO-B☆38Updated 3 months ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆460Updated last year
- {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch☆215Updated last month
- Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing☆46Updated 2 years ago