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A PyTorch implementation of "MetaFormer: A Unified Meta Framework for Fine-Grained Recognition". A reference PyTorch implementation of “CoAtNet: Marrying Convolution and Attention for All Data Sizes”
CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)
Fast, flexible and easy to use probabilistic modelling in Python.
Must-read papers on graph neural networks (GNN)
A library for efficient similarity search and clustering of dense vectors.
A blog for understanding graph neural network
Representation learning on large graphs using stochastic graph convolutions.
[AAAI-2020, Oral] Diversity Transfer Network for Few-Shot Learning
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
FAst Lookups of Cosine and Other Nearest Neighbors (based on fast locality-sensitive hashing)
Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle
MASS: Masked Sequence to Sequence Pre-training for Language Generation
An industrial deep learning framework for high-dimension sparse data
A custom OpenAI gym environment for simulating stock trades on historical price data.
Implementation of Optimal Auctions through Deep Learning
Python package built to ease deep learning on graph, on top of existing DL frameworks.
A collection of important graph embedding, classification and representation learning papers with implementations.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
The code for 2019 Tencent College Algorithm Contest, and the online result ranks 1st in the preliminary.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 论文的中文翻译 Chinese Translation!
Code for the paper "Language Models are Unsupervised Multitask Learners"
An implementation of training for GPT2, supports TPUs
Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search