danielkelshaw / ConcreteDropoutLinks
PyTorch implementation of 'Concrete Dropout'
☆16Updated last year
Alternatives and similar repositories for ConcreteDropout
Users that are interested in ConcreteDropout are comparing it to the libraries listed below
Sorting:
- A library for uncertainty quantification based on PyTorch☆121Updated 3 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated last month
- ☆152Updated 2 years ago
- Simple (and cheap!) neural network uncertainty estimation☆67Updated last month
- ☆31Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 4 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆130Updated 2 years ago
- Normalizing Flows using JAX☆83Updated last year
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated last year
- Pre-trained Gaussian processes for Bayesian optimization☆93Updated 3 months ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆16Updated 2 years ago
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆30Updated last year
- Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression on tabular data with tree-based diffusion …☆44Updated last month
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆130Updated last month
- Bayesian optimization with conformal coverage guarantees☆28Updated 2 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- A Python package for intrinsic dimension estimation☆91Updated 2 months ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Our maintained PFN repository. Come here to train SOTA PFNs.☆94Updated last week
- ☆240Updated 2 years ago
- ☆57Updated last year
- Large-scale, multi-GPU capable, kernel solver☆190Updated last year
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆221Updated 8 months ago
- Bayesian active learning with EPIG data acquisition☆32Updated 3 months ago
- Probabilistic Auto-Encoder☆43Updated 2 years ago