Solarica23

Solarica23's Stars

• 2018cx/SinKD

  Pytorch Implementation of "Sinkhorn Distance Minimization for Knowledge Distillation", COLING 2024

  Language:Python105

• changwxx/Awesome-Optimal-Transport-in-Deep-Learning

  a collection of AWESOME things about Optimal Transport in Deep Learning

  19518

• val-iisc/css-ccnn

  Implementation for "Completely Self-Supervised Crowd Counting via Distribution Matching" (http://arxiv.org/abs/2009.06420)

  Language:Python298

• sandareka/Interpretability-of-Machine-Learning-Visualizations

  Interpretability of Machine Learning-Visualizations

  Language:Python112

• LiJunnan1992/MLNT

  Meta-Learning based Noise-Tolerant Training

  Language:Python12329

• speechbrain/speechbrain

  A PyTorch-based Speech Toolkit

  Language:Python8.8k1.4k

• cure-lab/deep-active-learning

  An implementation of the state-of-the-art Deep Active Learning algorithms

  Language:Python9917

• cnguyen10/few_shot_meta_learning

  Implementations of many meta-learning algorithms to solve the few-shot learning problem in Pytorch

  Language:Python24429

• chenmc1996/Multi-Head-Co-Training

  The code for our AAAI 22 paper "Semi-Supervised Learning with Multi-Head Co-Training" and journal submission.

  Language:Python101

• sooftware/attentions

  PyTorch implementation of some attentions for Deep Learning Researchers.

  Language:Python51370

• google-research/mma

  Language:Python135

• Lightning-AI/litgpt

  20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

  Language:Python10.5k1k

• ej0cl6/deep-active-learning

  Deep Active Learning

  Language:Python807184

• Mephisto405/Learning-Loss-for-Active-Learning

  Reproducing experimental results of LL4AL [Yoo et al. 2019 CVPR]

  Language:Python21550

• beandkay/SequenceMatch

  Code for SequenceMatch (WACV 2024)

  Language:Python3

• TorchSSL/TorchSSL

  A PyTorch-based library for semi-supervised learning (NeurIPS'21)

  Language:Python1.3k186

• alinlab/PsCo

  Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning (ICLR 2023)

  Language:Python545

• cs-chan/ArtGAN

  ArtGAN + WikiArt: This work presents a series of new approaches to improve GAN for conditional image synthesis and we name the proposed model as “ArtGAN”.

  Language:Python41166

• db-Lee/Meta-GMVAE

  Language:Python397

• cmhungsteve/Awesome-Transformer-Attention

  An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

  4.6k489

• mwdhont/SimCLRv1-keras-tensorflow

  Tensorflow-Keras implementation of SimCLR: Simple Framework for Contrastive Learning of Visual Representations by Chen et al. (2020)

  Language:Jupyter Notebook11026

• BalajiAI/SimCLR

  PyTorch Implementation of "A Simple Framework for Contrastive Learning of Visual Representations". https://arxiv.org/pdf/2002.05709.pdf

  Language:Jupyter Notebook31

• Griffintaur/CLDA_NeurIPS21

  Language:Python101

• renmengye/few-shot-ssl-public

  Meta Learning for Semi-Supervised Few-Shot Classification

  Language:Python552100

• sekilab/RoadDamageDetector

  Language:Jupyter Notebook762256

• mani-shailesh/satimage

  Code and models for the manuscript "Predicting Poverty and Developmental Statistics from Satellite Images using Multi-task Deep Learning"

  Language:Python3521

• Xiyue-Wang/TransPath

  Language:Python26135

• zhangyikaii/PRML

  PRML algorithms implemented in Python

  Language:Jupyter Notebook22

• Frankluox/Channel_Importance_FSL

  [ICML 2022] Channel Importance Matters in Few-shot Image Classification

  Language:Python559

• jihoontack/SiMT

  Meta-Learning with Self-Improving Momentum Target (NeurIPS 2022)

  Language:Python232