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
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆35Updated 2 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 10 months ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- ☆53Updated 7 months ago
- Bayesian active learning with EPIG data acquisition☆28Updated last month
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆75Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆129Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 3 years ago
- Code for "The Intrinsic Dimension of Images and Its Impact on Learning" - ICLR 2021 Spotlight https://openreview.net/forum?id=XJk19XzGq2J☆68Updated 11 months ago
- Large-scale uncertainty benchmark in deep learning.☆53Updated last month
- Normalizing Flows using JAX☆82Updated last year
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- A PyTorch re-implementation of "Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives"☆18Updated 5 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- ☆98Updated 3 years ago
- Simple (and cheap!) neural network uncertainty estimation☆61Updated last month
- Riemannian Convex Potential Maps☆67Updated last year
- Instructions and examples to deploy some PyTorch code on slurm using a Singularity Container☆33Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆111Updated 2 years ago
- ☆36Updated 2 years ago
- Codebase for Learning Invariances in Neural Networks☆94Updated 2 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆66Updated 4 months ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated last year