kennethsible/confidence-estimation

Using Source-Side Confidence Estimation for Reliable Translation into Unfamiliar Languages

Language: Python - Size: 179 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0

scbirlab/duvida

🧐 Calculating exact and approximate confidence and information metrics for deep learning on general purpose and chemistry tasks.

Language: Python - Size: 196 KB - Last synced at: 20 days ago - Pushed at: 20 days ago - Stars: 0 - Forks: 0

kkirchheim/pytorch-ood

👽 Out-of-Distribution Detection with PyTorch

Language: Python - Size: 2.21 MB - Last synced at: about 1 month ago - Pushed at: about 2 months ago - Stars: 283 - Forks: 27

AmourWaltz/MlingConf

The project for MlingConf: A Comprehensive Investigation of Multilingual Confidence Estimation for Large Language Models

Language: Python - Size: 6.2 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

sleep3r/garrus

Python framework for high quality confidence estimation of deep neural networks, providing methods such as confidence calibration and ordinal ranking

Language: Python - Size: 79.1 KB - Last synced at: about 1 month ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

Kaimary/CKIF

KBS 2024 Paper, A Confidence-based Knowledge Integration Framework for Cross-Domain Table Question Answering

Language: Python - Size: 27.8 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 2 - Forks: 0

oracle/macest

Model Agnostic Confidence Estimator (MACEST) - A Python library for calibrating Machine Learning models' confidence scores

Language: Jupyter Notebook - Size: 11 MB - Last synced at: 5 days ago - Pushed at: over 1 year ago - Stars: 100 - Forks: 20

EQTPartners/sire

📈 SiRE (Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series Data), accepted by CIKM'2022 🗽

Language: Python - Size: 242 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 32 - Forks: 9

GiovanniCiampi/confidence_interval_estimator_ML

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.

Language: Jupyter Notebook - Size: 295 KB - Last synced at: 10 days ago - Pushed at: over 3 years ago - Stars: 5 - Forks: 0

pub-calculator-io/sample-size-calculator

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/

Language: JavaScript - Size: 7.36 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 15 - Forks: 0

alecokas/BiLatticeRNN-Confidence

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

Language: Python - Size: 614 KB - Last synced at: 16 days ago - Pushed at: about 5 years ago - Stars: 16 - Forks: 4

sanjaymjoshi/relistats

Computation of Reliability Statistics: Reliability, Confidence, Assurance

Language: Python - Size: 2.4 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

koulanurag/opcc

Benchmark for "Offline Policy Comparison with Confidence"

Language: Python - Size: 70.7 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

Impression2805/Awesome-Failure-Detection

A list of papers that studies out-of-distribution (OOD) detection and misclassification detection (MisD)

Size: 96.7 KB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 27 - Forks: 1

dschinagl/gace

Demo code for GACE: Geometry Aware Confidence Enhancement

Language: Python - Size: 756 KB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 7 - Forks: 0

osu-cvl/agriculture

Code for "Confidence-Driven Hierarchical Classification of Cultivated Plant Stresses"

Language: Python - Size: 27.3 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

Impression2805/FMFP

PyTorch implementation of our ECCV 2022 paper "Rethinking Confidence Calibration for Failure Prediction"

Language: Python - Size: 202 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 13 - Forks: 1

hspfatemeh/number-of-times-an-experiment-should-be-repeated-for-a-95-probability

number of times an experiment should be repeated for a 95% probability

Language: Jupyter Notebook - Size: 1.95 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

choshina/coverage-confidence

A Robustness-based Confidence Measure for Hybrid System Falsification

Language: HTML - Size: 31.7 MB - Last synced at: 5 months ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

g8a9/confidence_intervals

Simple evaluation of classification confidence intervals.

Language: Python - Size: 17.6 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

fabiotosi92/CCNN-Tensorflow

Learning from scratch a confidence measure

Language: Python - Size: 5.79 MB - Last synced at: about 2 years ago - Pushed at: about 6 years ago - Stars: 19 - Forks: 10

gsaygili/dimred

Source code for predicting confidence scores for the samples in t-sne embeddings.

Language: Python - Size: 233 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

insysbio/LikelihoodProfiler.py

Language: Python - Size: 6.99 MB - Last synced at: 6 months ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0

kheinrich93/LGC-Plus

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.

Language: Python - Size: 71.6 MB - Last synced at: 11 months ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 0

MultiTrickFox/UCB_MC

upper confidence bound improved w/ monte carlo

Language: Java - Size: 43.9 KB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0