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acl22-revisiting-uncertainty-based-query-strategies-for-active-learning-with-transformers

Revisiting Uncertainty-based Query Strategies for Active Learning with Transformers

active-learning

active-mixup

Code for Active Mixup in 2020 CVPR

active-prompt

Source code for the paper "Active Prompting with Chain-of-Thought for Large Language Models"

active_learning_coreset

Source code for ICLR 2018 Paper: Active Learning for Convolutional Neural Networks: A Core-Set Approach

actune

[NAACL 2022] This is the code repo for our paper `ACTUNE: Uncertainty-based Active Self-Training for Active Fine-Tuning of Pretrained Language Models'.

adversarial-representation-active-learning

Adversarial Representation Active Learning

al_ats

allrank

allRank is a framework for training learning-to-rank neural models based on PyTorch.

awesome-active-learning

A curated list of awesome Active Learning

awesome-ebm

Collecting research materials on EBM/EBL (Energy Based Models, Energy Based Learning)

awesome-knowledge-distillation

Awesome Knowledge Distillation

awesome-prompt-engineering

This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

badge

An implementation of the BADGE batch active learning algorithm.

balance

bandit_simulations

Bandit algorithms simulations for online learning

batchbald

Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning.

cm-acc

Cross-model active contrastive coding

contrastive-active-learning

Code for the EMNLP 2021 Paper "Active Learning by Acquiring Contrastive Examples" & the ACL 2022 Paper "On the Importance of Effectively Adapting Pretrained Language Models for Active Learning"

contrastive_learning_papers

A list of contrastive Learning papers

cords

Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.

coreset-al

A greedy implementation of coreset based active learning for image classification (https://arxiv.org/abs/1708.00489)

dagger

Dagger - An implementation of Dataset Aggregation

datamodels

datamodels-data

Data for "Datamodels: Predicting Predictions with Training Data"

datasciencecoursera

for Data Science class on Coursera

deep-active-learning

Deep Active Learning

deeplearning

Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

deepsets