izmailovpavel / neurips_bdl_starter_kit
☆18Updated last year
Alternatives and similar repositories for neurips_bdl_starter_kit:
Users that are interested in neurips_bdl_starter_kit are comparing it to the libraries listed below
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- ☆53Updated 9 months ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 11 months ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 3 years ago
- Bayesian active learning with EPIG data acquisition☆31Updated last week
- ☆99Updated 3 years ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆36Updated last week
- Laplace Redux -- Effortless Bayesian Deep Learning☆43Updated 2 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆75Updated last year
- Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)☆48Updated 3 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 10 months ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 5 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated last year
- Large-scale uncertainty benchmark in deep learning.☆56Updated 3 months ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆35Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 2 years ago
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆41Updated 2 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- This repository contains the Python code to reproduce all the figures and experiments presented in the paper: Masegosa, Andrés. R., Learn…☆9Updated 2 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆66Updated 5 months ago
- Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J☆68Updated last year
- Last-layer Laplace approximation code examples☆83Updated 3 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- Codebase for Learning Invariances in Neural Networks☆95Updated 2 years ago