506 Open source projects that are alternatives of or similar to DUN

(ICML 2022) Official PyTorch implementation of “Blurs Behave Like Ensembles: Spatial Smoothings to Improve Accuracy, Uncertainty, and Robustness”.

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Natural Gradient, Variational Inference

A collection of Methods and Models for various architectures of Artificial Neural Networks

Uncertainty-Wizard is a plugin on top of tensorflow.keras, allowing to easily and efficiently create uncertainty-aware deep neural networks. Also useful if you want to train multiple small models in parallel.

Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available

General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

A library for uncertainty quantification based on PyTorch

Code for the paper Implicit Weight Uncertainty in Neural Networks

Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation

Statistical Rethinking (2nd Ed) with Tensorflow Probability

GPstuff - Gaussian process models for Bayesian analysis

Julia package for automatic Bayesian inference on a factor graph with reactive message passing

PyTorch Implementations of Dropout Variants

A Latent Dirichlet Allocation implementation in Python.

Best practices for applying machine learning to bacterial 16S rRNA gene sequencing data

Open Source Photometric classification https://supernnova.readthedocs.io

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

Efficient, lightweight variational inference and approximation bounds

Deep universal probabilistic programming with Python and PyTorch

Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB

Modular Probabilistic Programming on MXNet

Scalable inference for a generative model of astronomical images

Collection of probabilistic models and inference algorithms

Unofficial Implementation of ECANets (CVPR 2020) for the Reproducibility Challenge 2020.

Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

Bayesian tools for fitting molecular mechanics torsion parameters to quantum chemical data.

Reusable, Easy-to-use Uncertainty module package built with Tensorflow, Keras

Using neural network to build expressive hierarchical distribution; A variational method to accurately estimate posterior uncertainty; A fast and general method for Bayesian inference. (ICML 2018)

Cross-disease comparison of case-control gut microbiome studies

Demultiplexing pooled scRNA-seq data with or without genotype reference

A pipeline for preprocessing NGS data from Illumina, Nanopore and PacBio technologies

A web interface for exploring PyMC3 traces

Blang's software development kit

A Deep Learning Approach to Ultrasound Image Recovery

Simultaneous Localization and Mapping(SLAM) also gives you a way to track the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, and other world features.

Sensor data aggregation tool for any numerical sensor data. Robust and privacy-friendly.

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

OpenCossan is an open and free toolbox for uncertainty quantification and management.

Bayesian spatial analysis

Empirical Software Engineering journal (EMSE) open science and reproducible research initiative

Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of survival models using both a frequentist approach (by calling the R package flexsurv) and a Bayesian perspective.

Uncertainty-aware principal component analysis.

CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification (ICCV2021)

Dirichlet Process K-means

An AutoDL tool for Neural Architecture Search and Hyperparameter Optimization on Tensorflow and Keras

WRENCH: Cyberinfrastructure Simulation Workbench

Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients"

Reachability analysis for closed-loop control systems

Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning, ICLR 2020

The GenePattern Server web application

Manager for multi-container computing environments

ukbREST: efficient and streamlined data access for reproducible research of large biobanks

A research library for pytorch-based neural network pruning, compression, and more.

Transformations to contrained variables from ℝⁿ.

Parallel random matrix tools and complexity for deep learning

Material for a Bayesian statistics workshop