data-efficient
There are 18 repositories under data-efficient topic.
mit-han-lab/data-efficient-gans
[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
mahmoodlab/CLAM
Open source tools for computational pathology - Nature BME
google/lecam-gan
Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)
MarvinLer/tcga_segmentation
Whole Slide Image segmentation with weakly supervised multiple instance learning on TCGA | MICCAI2020 https://arxiv.org/abs/2004.05024
VITA-Group/Ultra-Data-Efficient-GAN-Training
[NeurIPS'21] "Ultra-Data-Efficient GAN Training: Drawing A Lottery Ticket First, Then Training It Toughly", Tianlong Chen, Yu Cheng, Zhe Gan, Jingjing Liu, Zhangyang Wang
layumi/AdaBoost_Seg
TIP2022 Adaptive Boosting (AdaBoost) for Domain Adaptation ? :woman_shrugging: Why not ! :ok_woman:
zjunlp/RAP
[SIGIR 2023] Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction
lizhaoliu-Lec/CG-VLM
This is the official repo for Contrastive Vision-Language Alignment Makes Efficient Instruction Learner.
Linxyhaha/DEALRec
Data-efficient Fine-tuning for LLM-based Recommendation (SIGIR'24)
theolepage/ssl-for-slr
Collection of self-supervised models for speaker and language recognition tasks.
4m4n5/CLIP-Lite
Pytorch Implementation of CLIP-Lite | Accepted at AISTATS 2023
MichiganNLP/micromodels
Micromodels -- A framework for accurate, explainable, data efficient, and reusable NLP models.
VITA-Group/Data-Efficient-Scaling
[ICML 2023] "Data Efficient Neural Scaling Law via Model Reusing" by Peihao Wang, Rameswar Panda, Zhangyang Wang
VITA-Group/Double-Win-LTH
[ICML 2022] "Data-Efficient Double-Win Lottery Tickets from Robust Pre-training" by Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang
GU-DataLab/misinformation-detection-DeMis
Resource for misinformation research on Twitter. Official resource of the paper "DeMis: Data-efficient Misinformation Detection using Reinforcement Learning", ECML-PKDD 2022
parshakova/GAMS-for-Data-Efficient-Learning
Global Autoregressive Models (GAMs) for Data-Efficient Sequence Learning
SahilC/knowledge-distill-fine-grained
Code for the Knowledge distillation work to enhance fine grained disease recognition.
hubtru/ASCDomain
Data loader and solution method for the DCASE 2024 Challenge Task1