GitHub

uqlm: Uncertainty Quantification for Language Models

UQLM provides a suite of response-level scorers for quantifying the uncertainty of Large Language Model (LLM) outputs. Each scorer returns a confidence score between 0 and 1, where higher scores ...
IEEE

Estimating Multi-Label Expected Accuracy Using Labelset Distributions

Abstract: A multi-label classifier estimates the binary label state (relevant/irrelevant) for each of a set of concept labels, for a given instance. Probabilistic multi-label classifiers provide a ...
IEEE

Multi-label Bird Species Classification Using Ensemble of Pre-trained Networks

Abstract: Birds are crucial to the ecosystem's optimum functioning since they maintain a stable climate, convert toxins into nutrients, and oxygenate the atmosphere. Identifying multiple bird species ...
GitHub

Python package to parse, analyse, and plot Apple HealthKit data

The Apple Health Parser Python package simplifies the extraction and analysis of health data exported from Apple HealthKit. Designed for seamless integration into data science workflows and health ...