active-learning

Llibre enfocat per als estudiants que desitgen ampliar els seus coneixements en sistemes operatius mitjançant una aproximació pràctica i orientada a Debian.

Deep active-learning & semi-supervised image classification on CIFAR-10 (ResNet + TypiClust selection, PyTorch)

This is a repository for CS4ML. It is a general framework for active learning in regression problems. It approximates a target function arising from general types of data, rather than pointwise samples.

Code, processed annotations, and research systems for MUST-Rank active preference refinement.

A Simulação de Grandezas Geométricas tem o objetivo que o aluno possa explorar as formas geométricas e observar as relações entre suas propriedades e conceitos matemáticos

A premium media & RSS aggregator with dynamic serendipity curation, pgvector semantic discovery, auto YouTube URL/handle resolver, telemetry active-learning, and React animations.

Making text analysis and topic ontology creation easier

Implementation of the paper : http://www.aclweb.org/anthology/N15-1047

NSE and random sampling strategies comparison for active learning

A Robust Active Learning Framework for Graph Anomaly Detection (GAD). Optimized implementation of GraphPart adapted for class-imbalance scenarios, supporting datasets like Weibo, Reddit, and Enron.

Benchmark of 11 Active Learning strategies on Fashion-MNIST (PyTorch): uncertainty sampling, BALD, and post-hoc calibration (Temperature Scaling, MC Dropout). 2× label efficiency over random baseline.

Python module for Catalysts' Degradation navigated by US

A CNN trained from scratch to track an object nearly the same color as its background, on a bad camera, from ~180 hand-labeled frames.

PFN Probe: cost-aware sequential feature acquisition with STOP for TabPFN-3.5

Adaptive surrogate Bayesian inversion for expensive black-box models with MPI, PyTorch, and HMC

Train a retail price-tag detector with zero hand-labeling — teacher-student bootstrap over public models and data (YOLOv11 → ONNX)

Distributed Active Learning using Apache Spark and MLlib, combining uncertainty sampling and diversity-based selection.