qibinc

JoyMapperSilicon

Nintendo Joy-Con / Pro Controller Mapper for Apple silicon

RecipeReduce

RecipeReduce: Simplified Recipe Processing for Lazy Programmers

KOBE

Towards Knowledge-Based Personalized Product Description Generation in E-commerce @ KDD 2019

baselines

A collection of baselines for the MineRL environment/datasets & the NeurIPS 2019 MineRL competition

CogQA

Cognitive Graph for Multi-Hop Reading Comprehension at Scale

fast-transformers-1

Pytorch library for fast transformer implementations

interviews.ai

It is my belief that you the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.

11-767

Course materials for 11-767

AMiniMiner

awesome-phd-advice

Collection of advice for prospective and current PhD students

BLIP

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

cmustrudel.github.io

Lab website

code-server

VS Code in the browser

cogdl

CogDL: An Extensive Research Toolkit for Graphs

cogdl-leaderboard

Detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

detectron2

Detectron2 is FAIR's next-generation research platform for object detection and segmentation.

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

dotfiles

IdBench

A benchmark for evaluating embeddings of identifiers in source code.

Kick-Start

MultiHopKG

Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout

OFA

Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

ogb

Benchmark datasets, data loaders, and evaluators for graph machine learning

qibinc.github.io

releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

transformers

🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

us-visa

预约美帝签证各个签证处最早时间的爬虫

VarCLR

VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning

xformer-multi-source-domain-adaptation

Code to reproduce the experiments in the paper "Transformer Based Multi-Source Domain Adaptation" (EMNLP 2020)