The open-source tool for building high-quality datasets and computer vision models
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Updated
Jul 16, 2024 - Python
The open-source tool for building high-quality datasets and computer vision models
Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
DiverGen (CVPR 2024) & BSGAL (ICML 2024)
Active Learning Method for Virtual Support Vector Machine with self-learning constraints
The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field
Active learning for systematic reviews
INCEpTION provides a semantic annotation platform offering intelligent annotation assistance and knowledge management.
Experimental design and (multi-objective) bayesian optimization.
Bayesian Optimization and Design of Experiments
PotentialLearning.jl: Optimize your atomistic data and interatomic potential models in your molecular dynamic workflows.
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.
List of protein (enzymes, antibody, and PPIs) conformations and molecular dynamics using generative artificial intelligence and deep learning
Explanation system for semi-supervised multi-objective optimization
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Quantile set inversion [arXiv:2211.01008] — Numerical experiments
Specificy, execute and monitor performances of active learning pipelines.
A Python library with utilities for Machine Learning research and algorithm implementations
Smarter Manual Annotation for Resource-constrained collection of Training data
Active Learning for Text Classification in Python
Awesome Active Domain Adaptation for Medical Image Analysis
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