ShellingFord221 / My-implementation-of-What-Uncertainties-Do-We-Need-in-Bayesian-Deep-Learning-for-Computer-VisionView on GitHub
Pytorch implementation of classification task in What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision (simple version)
☆79Jul 13, 2021Updated 4 years ago
Alternatives and similar repositories for My-implementation-of-What-Uncertainties-Do-We-Need-in-Bayesian-Deep-Learning-for-Computer-Vision
Users that are interested in My-implementation-of-What-Uncertainties-Do-We-Need-in-Bayesian-Deep-Learning-for-Computer-Vision are comparing it to the libraries listed below
Sorting:
- Pytorch implementation of "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"☆171Jun 27, 2019Updated 6 years ago
- "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).☆209Dec 19, 2019Updated 6 years ago
- Uncertainty quantification using Bayesian neural networks in classification (MIDL 2018, CSDA)☆137Jul 30, 2019Updated 6 years ago
- ☆239May 23, 2020Updated 5 years ago
- Depth to normals preprocessing tool with Python and CUDA support for CVPR2019 paper 1899: DeepLiDAR: Deep Surface Normal Guided Depth Pre…☆11Jun 19, 2020Updated 5 years ago
- code for the paper "ADAPT: Vision-Language Navigation with Modality-Aligned Action Prompts" (CVPR 2022)☆10Jul 17, 2022Updated 3 years ago
- Code for our MIDL2020 submission "Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning".☆32Apr 27, 2021Updated 4 years ago
- Official implementation of the NeurIPS 2023 paper: "Uncertainty Quantification via Neural Posterior Principal Components"☆13Jun 18, 2024Updated last year
- DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction with Deep T1 Prior (CVPR 2020)☆59Jun 22, 2020Updated 5 years ago
- Building a Bayesian deep learning classifier☆494Oct 30, 2017Updated 8 years ago
- Stochastic Segmentation Networks☆67Jun 26, 2020Updated 5 years ago
- ☆113Jun 2, 2023Updated 2 years ago
- A PyTorch implementation of EMANet based on ICCV 2019 paper "Expectation-Maximization Attention Networks for Semantic Segmentation"☆18Feb 21, 2020Updated 6 years ago
- DKN code☆44Oct 21, 2019Updated 6 years ago
- Codebase for SEFS: Self-Supervision Enhanced Feature Selection with Correlated Gates☆24Sep 11, 2023Updated 2 years ago
- [ACMMM 2020] Code release for "Learning Deep Multimodal Feature Representation with Asymmetric Multi-layer Fusion"☆28Aug 19, 2021Updated 4 years ago
- [AIIM'22] The official code for "Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentation"☆25Dec 21, 2022Updated 3 years ago
- The official code repo for the paper "Mixture of Stochastic Experts for Modeling Aleatoric Uncertainty in Segmentation". (ICLR 2023)☆29Jun 27, 2023Updated 2 years ago
- Code for the paper "End-to-end training of deep probabilistic CCA on paired biomedical observations".☆28May 18, 2021Updated 4 years ago
- Dropout as Regularization and Bayesian Approximation☆56Nov 17, 2018Updated 7 years ago
- ☆25Aug 11, 2022Updated 3 years ago
- Single Image Reflection Removal based on GAN with Gradient Constraint (GCNet)☆27Jan 14, 2020Updated 6 years ago
- Implementation of Optimal Transport-driven CycleGAN (OT-CycleGAN)☆22Jan 10, 2022Updated 4 years ago
- This is an example program illustrating BERTs masked language model.☆28Oct 8, 2020Updated 5 years ago
- Uncertainty in Medical Image Analysis☆318Nov 6, 2021Updated 4 years ago
- This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning mo…☆787Dec 5, 2025Updated 3 months ago
- Implementation of the MNIST experiment for Monte Carlo Dropout from http://mlg.eng.cam.ac.uk/yarin/PDFs/NIPS_2015_bayesian_convnets.pdf☆30Jan 15, 2020Updated 6 years ago
- ☆27Aug 12, 2021Updated 4 years ago
- The Official PyTorch Implementation of OTSeg: Multi-prompt Sinkhorn Attention for Zero-Shot Semantic Segmentation☆34Jul 6, 2024Updated last year
- Code for experiments to learn uncertainty☆30Mar 16, 2023Updated 2 years ago
- Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.☆1,567Apr 19, 2024Updated last year
- High-quality implementations of standard and SOTA methods on a variety of tasks.☆1,567Feb 2, 2026Updated last month
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Mar 17, 2022Updated 3 years ago
- Towards performant and reliable undersampled MR reconstruction via diffusion model sampling☆66Feb 9, 2023Updated 3 years ago
- ☆34Nov 24, 2021Updated 4 years ago
- This is official Pytorch implementation of "Uncertainty quantification in medical image segmentation with Normalizing Flows", Raghavendra…☆30Oct 23, 2022Updated 3 years ago
- [NeurIPS 2020] Disentangling Human Error from the Ground Truth in Segmentation of Medical Images☆74Apr 25, 2023Updated 2 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Apr 23, 2024Updated last year
- Implementation for flowwalk☆33Mar 27, 2022Updated 3 years ago