Popular GitHub Repositories for Upper Confidence Bounds

Multilingual Automatic Speech Recognition with word-level timestamps and confidence

ARCH models in Python

We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the

UQLM: Uncertainty Quantification for Language Models, is a Python package for UQ-based LLM hallucination detection

Python package for conformal prediction

Learn fast, scalable, and calibrated measures of uncertainty using neural networks!

auto_LiRPA: An Automatic Linear Relaxation based Perturbation Analysis Library for Neural Networks and General Computational Graphs

? Out-of-Distribution Detection with PyTorch

A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.

Confidence and Byt5 - based geotagging model predicting coordinates from text alone.

Official Implementation for the "Conffusion: Confidence Intervals for Diffusion Models" paper.

Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTorch).

[Materials & Design 2024] A Bayesian global optimization package for material design ｜ Adaptive Learning | Active Learning

The official implementation of "CAME: Confidence-guided Adaptive Memory Optimization"

Outlier Exposure with Confidence Control for Out-of-Distribution Detection

MCP server for agents to explore rust docs, analyze source code, and build with confidence

PyTorch Code for running various time series models for different time stamps and confidence intervals for Solar Irradiance prediction.

Prediction of respiratory diseases such as COPD(Chronic obstructive pulmonary disease), URTI(upper respiratory tract infection), Bronchiectasis, Pneumonia, Bronchiolitis with the help of deep neural networks or deep learning. We have constructed a deep neural network model that takes in respiratory sound as input and classifies the condition of its respiratory system. It not only classifies among the above-mentioned disease but also classifies if a person’s respiratory system is healthy or not with higher accuracy and precision.

Build production-ready AI agents in days, not months. Python 3.13+. Save development time with minimal code, deploy anywhere with confidence, and scale from simple assistants to complex multi-agent systems without the headaches.

Efficient, lightweight variational inference and approximation bounds