Dante1995Wang

Dante1995Wang's Stars

• 0voice/expert_readed_books

  2021年最新总结，推荐工程师合适读本，计算机科学，软件技术，创业，**类，数学类，人物传记书籍

  9.2k178132.8k

• deepchem/deepchem

  Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

  Language:Python5.6k1451.7k1.7k

• floodsung/Meta-Learning-Papers

  Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

  2.6k1693475

• median-research-group/LibMTL

  A PyTorch Library for Multi-Task Learning

  Language:Python2.1k1982198

• tristandeleu/pytorch-meta

  A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

  Language:Python2k44141256

• invictus717/MetaTransformer

  Meta-Transformer for Unified Multimodal Learning

  Language:Python1.6k2268116

• sudharsan13296/Awesome-Meta-Learning

  A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.

  1.5k692297

• brendenlake/omniglot

  Omniglot data set for one-shot learning

  Language:MATLAB1.4k450357

• floodsung/LearningToCompare_FSL

  PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)

  Language:Python1.1k3244265

• orobix/Prototypical-Networks-for-Few-shot-Learning-PyTorch

  Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch

  Language:Python9991425210

• megvii-research/BBN

  The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition

  Language:Python6621229103

• Vanint/Awesome-LongTailed-Learning

  A codebase and a curated list of awesome deep long-tailed learning (TPAMI 2023).

  Language:Python51915165

• jma127/pyltr

  Python learning to rank (LTR) toolkit

  Language:Python4651714107

• lucidrains/egnn-pytorch

  Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

  Language:Python43881974

• tristandeleu/ntm-one-shot

  One-shot Learning with Memory-Augmented Neural Networks

  Language:Python421291894

• tristandeleu/pytorch-maml

  An Implementation of Model-Agnostic Meta-Learning in PyTorch with Torchmeta

  Language:Python232112044

• Raschka-research-group/coral-pytorch

  CORAL and CORN implementations for ordinal regression with deep neural networks.

  Language:Python22661224

• markdtw/meta-learning-lstm-pytorch

  pytorch implementation of Optimization as a Model for Few-shot Learning

  Language:Python17831135

• microsoft/FS-Mol

  FS-Mol is A Few-Shot Learning Dataset of Molecules, containing molecular compounds with measurements of activity against a variety of protein targets. The dataset is presented with a model evaluation benchmark which aims to drive few-shot learning research in the domain of molecules and graph-structured data.

  Language:Python162121123

• kaize0409/awesome-few-shot-gnn

  An index of algorithms for few-shot learning/meta-learning on graphs

  1457018

• zhichunguo/Meta-MGNN

  Few-Shot Graph Learning for Molecular Property Prediction

  Language:Python1365831

• molecule-generator-collection/ChemTSv2

  Refined and extended version of ChemTS

  Language:Python8851621

• rasbt/DeepLearning-Gdansk2019-tutorial

  Ordinal Regression tutorial for the International Summer School on Deep Learning 2019

  Language:Jupyter Notebook689017

• mattochal/imbalanced_fsl_public

  PyTorch implementation for "Few-Shot Learning with Class Imbalance"

  Language:Python35526

• rcmalli/lightning-maml

  MAML Implementation using Pytorch-lightning

  Language:Python21235

• HICAI-ZJU/GS-Meta

  Code and Data for the paper: Graph Sampling-based Meta-Learning for Molecular Property Prediction [IJCAI2023]

  Language:Python18232

• danielvlla/Few-Shot-Learning-for-Low-Data-Drug-Discovery

  Few-shot machine learning for low-data drug discovery.

  Language:Jupyter Notebook17205

• Masatsugar/graph-decomposition-reassembling

  Language:Python7201

• winterxx/ACE

  code for paper [ACE: Ally Complementary Experts for Solving Long-Tailed Recognition in One-Shot] (ICCV 2021, oral))

  Language:Python6103

• javierbg/ordinal-losses

  Implementation of ordinal losses for neural networks.

  Language:Python10