Topic: uncertainty-neural-networks Goto Github
Some thing interesting about uncertainty-neural-networks
Some thing interesting about uncertainty-neural-networks
uncertainty-neural-networks,Dataset and code for "Uncertainty-Informed Deep Transfer Learning of PFAS Toxicity"
Organization: ai4pfas
uncertainty-neural-networks,Implementation of the MNIST experiment for Monte Carlo Dropout from http://mlg.eng.cam.ac.uk/yarin/PDFs/NIPS_2015_bayesian_convnets.pdf
User: alexrakowski
uncertainty-neural-networks,A list of papers on Active Learning and Uncertainty Estimation for Neural Networks.
User: amrit110
uncertainty-neural-networks,PyTorch implementation of Probabilistic MIMO U-Net
User: antonbaumann
uncertainty-neural-networks,A repository about Robust Deep Neural Networks with Uncertainty, Local Competition and Error-Correcting-Output-Codes in TensorFlow.
User: antonyalexos
uncertainty-neural-networks,ML framework to estimate Bayesian posteriors of galaxy morphological parameters
User: aritraghsh09
Home Page: http://gampen.ghosharitra.com/
uncertainty-neural-networks,Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)
Organization: cambridge-mlg
uncertainty-neural-networks,[WACV'22] Official implementation of "HHP-Net: A light Heteroscedastic neural network for Head Pose estimation with uncertainty"
User: cantarinigiorgio
uncertainty-neural-networks,A repo for toy examples to test uncertainties estimation of neural networks
User: cdebeunne
uncertainty-neural-networks,Code and supporting materials for the ICLR 2020 RIO paper
Organization: cognizant-ai-labs
uncertainty-neural-networks,Official code for "Enabling Uncertainty Estimation in Iterative Neural Networks" (ICML 2024)
Organization: cvlab-epfl
Home Page: https://www.norange.io/projects/unc_iter/
uncertainty-neural-networks,Probabilistic framework for solving Visual Dialog
Organization: delta-lab-iitk
uncertainty-neural-networks,A project to train your model from scratch or fine-tune a pretrained model using the losses provided in this library to improve out-of-distribution detection and uncertainty estimation performances. Calibrate your model to produce enhanced uncertainty estimations. Detect out-of-distribution data using the defined score type and threshold.
User: dlmacedo
uncertainty-neural-networks,Official Code: Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes
Organization: dlr-rm
uncertainty-neural-networks,This repository is for implementation of the paper Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles. This algorithm quantifies predictive predictive uncertainty in non-Bayesian NN with Deep Ensemble Model. Contribution of this paper is that it describes simple and scalable method for estimating predictive uncertainty estimates from NN.
User: dlwptmd001
uncertainty-neural-networks,This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"
User: dougbrion
Home Page: http://arxiv.org/abs/1806.01768
uncertainty-neural-networks,A CNN based Depth, Optical Flow, Flow Uncertainty and Camera Pose Prediction pipeline
User: dthanuja
uncertainty-neural-networks,This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.
Organization: ensta-u2is-ai
uncertainty-neural-networks,This repository provides the official implementation of "Robust channel-wise illumination estimation." accepted in BMVC (2021).
User: firasl
uncertainty-neural-networks,The second-moment loss (SML) is a novel training objective for dropout-based regression networks that yields improved uncertainty estimates.
Organization: fraunhofer-iais
uncertainty-neural-networks,Inferring distributions over depth from a single image, IROS 2019
User: gengshan-y
Home Page: https://gengshan-y.github.io/monodepth-uncertainty/
uncertainty-neural-networks,To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective than the classifier's own implied confidence (e.g. softmax probability for a neural network).
Organization: google
Home Page: https://arxiv.org/abs/1805.11783
uncertainty-neural-networks,Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.
Organization: intellabs
uncertainty-neural-networks,A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch
Organization: intellabs
uncertainty-neural-networks,Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
User: javierantoran
uncertainty-neural-networks,
User: jerinphilip
uncertainty-neural-networks,This repository contains code and resources for my thesis project on uncertainty estimation in computed tomography (CT) scan modeling. Explore Bayesian and deterministic neural network architectures for CT analysis and compare their effectiveness in quantifying uncertainty.
User: juanfierro94
uncertainty-neural-networks,Model zoo for different kinds of uncertainty quantification methods used in Natural Language Processing, implemented in PyTorch.
User: kaleidophon
Home Page: http://dennisulmer.eu/nlp-uncertainty-zoo/
uncertainty-neural-networks,A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. More details: "A Primer on Bayesian Neural Networks: Review and Debates"
User: konstantinos-p
Home Page: https://arxiv.org/abs/2309.16314
uncertainty-neural-networks,Uncertainty quantification fo ML - collection of scripts, tutorials and templates
User: kyaiooiayk
uncertainty-neural-networks,Attempt to reproduce the toy experiment of http://bit.ly/2C9Z8St with an ensemble of nets and with dropout.
User: marcovirgolin
uncertainty-neural-networks,NOMU: Neural Optimization-based Model Uncertainty
Organization: marketdesignresearch
Home Page: https://arxiv.org/abs/2102.13640
uncertainty-neural-networks,This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as described in "A General Framework for Uncertainty Estimation in Deep Learning" (Loquercio, SegΓΉ, Scaramuzza. RA-L 2020).
User: mattiasegu
uncertainty-neural-networks,Probabilistic load forecasting with Reservoir Computing
User: micheleuit
uncertainty-neural-networks,Benchmarking uncertainty quantification methods on proteins.
Organization: microsoft
uncertainty-neural-networks,Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).
User: nikitadurasov
Home Page: https://www.norange.io/projects/masksembles/
uncertainty-neural-networks,Code for "Deal: Deep Evidential Active Learning for Image Classification" (ICMLA 2020)
User: ptrckhmmr
uncertainty-neural-networks,Observations and notes to understand the workings of neural network models and other thought experiments using Tensorflow
User: shekkizh
uncertainty-neural-networks,Example Git repository that you can run on the signaloid.io uncertainty-tracking computation platform.
Organization: signaloid
uncertainty-neural-networks,A validation study for the application of quantile regression neural networks to Bayesian remote sensing retrievals
User: simonpf
uncertainty-neural-networks,RBF SVM based wrong prediction estimator in deep learning models employed for CPS data
Organization: simula-complex
uncertainty-neural-networks,An implementation of natural parameter networks and its extension to GRUs in PyTorch
User: sohamghosh121
uncertainty-neural-networks,A pytorch implementation of MCDO(Monte-Carlo Dropout methods)
User: sungyubkim
uncertainty-neural-networks,Guided Perturbations: Self-Corrective Behavior in Convolutional Neural Networks
User: swamiviv
uncertainty-neural-networks,NeurIPS paper 'Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis'
User: teapearce
uncertainty-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.
Organization: testingautomated-usi
Home Page: https://uncertainty-wizard.readthedocs.io
uncertainty-neural-networks,Official implementation of the AIAA Journal paper "Uncertainty-aware Surrogate Models for Airfoil Flow Simulations with Denoising Diffusion Probabilistic Models"
Organization: tum-pbs
uncertainty-neural-networks,UAP-BEV: Uncertainty Aware Planning in Bird's Eye View Generated from Monocular Images (CASE 2023)
User: vikr-182
Home Page: https://vikr-182.github.io/UAP-BEV/
uncertainty-neural-networks,My implementation of the paper "Simple and Scalable Predictive Uncertainty estimation using Deep Ensembles"
User: vvanirudh
uncertainty-neural-networks,Uncertainty aware brain age prediction
Organization: wwu-mmll
Home Page: https://photon-ai.com/model_repo/uncertainty-brain-age
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