Ziniu Hu (acbull)

acbull

Geek Repo

Company:@xai-org

Location:Palo Alto

Home Page:http://acbull.github.io

Github PK Tool:Github PK Tool


Organizations
UCLA-DM

Ziniu Hu's repositories

pyHGT

Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric

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GPT-GNN

Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"

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Unbiased_LambdaMart

Code for WWW'19 "Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm", which is based on LightGBM

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LADIES

Code for NeurIPS'19 "Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks"

HGT-DGL

Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on Deep Graph Library (DGL)

HiCE

Code for ACL'19 "Few-Shot Representation Learning for Out-Of-Vocabulary Words"

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awesome-computer-vision

A curated list of awesome computer vision resources

awesome-llm-powered-agent

Awesome things about LLM-powered agents. Papers / Repos / Blogs / ...

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CS285-RL-study

Course Study Material for UCB CS285: Deep Reinforcement Learning

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ArknightsGameData

明日方舟游戏数据

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awesome-neural-programming

A curated list of awesome neural programming resources

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backend

Penguin Statistics backend.

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CapsGNN

A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

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CS249

Course Project For UCLA CS249

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CSrankings

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

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dgl

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

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ELSA

Code for "Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification"

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GCC

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

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ogb

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

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Paladin

Automated Generation of Reproducible Test Cases for Android Apps

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pytorch_scatter

PyTorch Extension Library of Optimized Scatter Operations

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transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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