data-efficient-learning

There are 13 repositories under data-efficient-learning topic.

  • BIT-DA/RIPU

    [CVPR 2022 Oral] Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation https://arxiv.org/abs/2111.12940

    Language:Python1397520

  • ChandlerBang/GCond

    [ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"

    Language:Python11841817
  • spear

    decile-team/spear

    SPEAR: Programmatically label and build training data quickly.

    Language:Jupyter Notebook10310220

  • licongguan/ILM-ASSL

    Iterative Loop Method Combining Active and Semi-Supervised Learning for Domain Adaptive Semantic Segmentation

    Language:Python324103

  • lizhaoliu-Lec/CPCM

    This is the official repo for Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation (ICCV 23).

    Language:Python323133

  • cvjena/deic

    Benchmark for Data-Efficient Image Classification

    Language:Jupyter Notebook23303

  • lizhaoliu-Lec/CG-VLM

    This is the official repo for Contrastive Vision-Language Alignment Makes Efficient Instruction Learner.

    21441

  • lorenzobrigato/gem

    A Pytorch-based library to evaluate learning methods on small image classification datasets

    Language:Jupyter Notebook15114

  • VITA-Group/DataEfficientLTH

    [NeurIPS 2022] "Sparse Winning Tickets are Data-Efficient Image Recognizers" by Mukund Varma T, Xuxi Chen, Zhenyu Zhang, Tianlong Chen, Subhashini Venugopalan, Zhangyang Wang

    Language:Python71101

  • srsawant34/efficient_instruction_learning

    Code base for the paper "Instruction Tuned Models are Quick Learners".

    Language:Python6302

  • visresearch/dems

    This repository includes official implementation and model weights of Data-Efficient Multi-Scale Fusion Vision Transformer.

    Language:Python6200

  • NUS-LID/RENAULT

    Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning

    Language:Python1200
  • MINING-GOLD-FROM-GENERATORS

    leonrenn/MINING-GOLD-FROM-GENERATORS

    Mining gold from implicit models to improve likelihood-free inference, example for ROLR and RASCAL.

    Language:Jupyter Notebook0100