AlaaLab / deep-learning-uncertaintyLinks
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
☆633Updated 3 years ago
Alternatives and similar repositories for deep-learning-uncertainty
Users that are interested in deep-learning-uncertainty are comparing it to the libraries listed below
Sorting:
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆474Updated 2 years ago
- ☆239Updated 5 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Updated 3 years ago
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,551Updated last month
- Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"☆576Updated 3 years ago
- Building a Bayesian deep learning classifier☆492Updated 8 years ago
- Bayesian Deep Learning Benchmarks☆672Updated 2 years ago
- Bayesian Deep Learning: A Survey☆517Updated last month
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆369Updated last year
- Learn fast, scalable, and calibrated measures of uncertainty using neural networks!☆499Updated 4 years ago
- This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"☆503Updated last year
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- PyTorch implementation of bayesian neural network [torchbnn]☆552Updated last year
- ☆109Updated 4 years ago
- Papers for Bayesian-NN☆326Updated 6 years ago
- ☆251Updated 2 years ago
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆638Updated 7 months ago
- Reliability diagrams visualize whether a classifier model needs calibration☆161Updated 3 years ago
- A simple and extensible library to create Bayesian Neural Network layers on PyTorch.☆980Updated 2 years ago
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆206Updated 3 years ago
- Open-source framework for uncertainty and deep learning models in PyTorch☆451Updated last month
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,542Updated last year
- ☆471Updated last month
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆254Updated 2 years ago
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆151Updated 3 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 6 years ago
- Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more☆1,943Updated 2 years ago
- Laplace approximations for Deep Learning.☆528Updated 7 months ago
- A simple way to calibrate your neural network.☆1,167Updated 4 months ago