Topic: confidence-estimation Goto Github
Some thing interesting about confidence-estimation
Some thing interesting about confidence-estimation
confidence-estimation,Confidence Estimation for Black Box Automatic Speech Recognition Systems Using Lattice Recurrent Neural Networks https://arxiv.org/abs/1910.11933 or https://ieeexplore.ieee.org/document/9053264
User: alecokas
confidence-estimation,A Robustness-based Confidence Measure for Hybrid System Falsification
User: choshina
confidence-estimation,Official pytorch implementation of the paper [Adaptive confidence thresholding for monocular depth estimation]
User: doihye
confidence-estimation,Demo code for GACE: Geometry Aware Confidence Enhancement
User: dschinagl
confidence-estimation,📈 SiRE (Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series Data), accepted by CIKM'2022 🗽
Organization: eqtpartners
confidence-estimation,Learning from scratch a confidence measure
User: fabiotosi92
confidence-estimation,Simple evaluation of classification confidence intervals.
User: g8a9
confidence-estimation,This repo contains code to perform Bootstrap Confidence Intervals estimation (a.k.a. Monte Carlo Confidence Interval or Empirical Confidence Interval estimation) for Machine Learing models.
User: giovanniciampi
confidence-estimation,Source code for predicting confidence scores for the samples in t-sne embeddings.
User: gsaygili
confidence-estimation,number of times an experiment should be repeated for a 95% probability
User: hspfatemeh
confidence-estimation,A list of papers that studies out-of-distribution (OOD) detection and misclassification detection (MisD)
User: impression2805
confidence-estimation,PyTorch implementation of our ECCV 2022 paper "Rethinking Confidence Calibration for Failure Prediction"
User: impression2805
confidence-estimation,
Organization: insysbio
Home Page: https://insysbio.github.io/LikelihoodProfiler.py/
confidence-estimation,In recent years, the ability to assess the uncertainty of depth estimates in the context of dense stereo matching has received increased attention due to its potential to detect erroneous estimates. Especially, the introduction of deep learning approaches greatly improved general performance, with feature extraction from multiple modalities proving to be highly advantageous due to the unique and different characteristics of each modality. However, most work in the literature focuses on using only mono- or bi- or rarely tri-modal input, not considering the potential effectiveness of modalities, going beyond tri-modality. To further advance the idea of combining different types of features for confidence estimation, in this work, a CNN-based approach is proposed, exploiting uncertainty cues from up to four modalities.
User: kheinrich93
confidence-estimation,👽 Out-of-Distribution Detection with PyTorch
User: kkirchheim
Home Page: https://pytorch-ood.readthedocs.io/
confidence-estimation,Benchmark for "Offline Policy Comparison with Confidence"
User: koulanurag
Home Page: https://koulanurag.dev/opcc
confidence-estimation,upper confidence bound improved w/ monte carlo
User: multitrickfox
confidence-estimation,Model Agnostic Confidence Estimator (MACEST) - A Python library for calibrating Machine Learning models' confidence scores
Organization: oracle
confidence-estimation,Code for "Confidence-Driven Hierarchical Classification of Cultivated Plant Stresses"
Organization: osu-cvl
confidence-estimation,Free WordPress Plugin: This sample size calculator enables you to calculate the minimum sample size and the margin of error. Learn about sample size, the margin of error, & confidence interval. www.calculator.io/sample-size-calculator/
Organization: pub-calculator-io
Home Page: https://www.calculator.io/sample-size-calculator/
confidence-estimation,Computation of Reliability Statistics: Reliability, Confidence, Assurance
User: sanjaymjoshi
Home Page: https://github.com/sanjaymjoshi/relistats
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.