liucsthu

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

apl

Open source implementation of Adaptive Posterior Learning (ICLR 2019)

attention-is-all-you-need-pytorch

A PyTorch implementation of the Transformer model in "Attention is All You Need".

AutoPrescribe

Learning to Prescribe

awesome-graph-explainability-papers

Papers about explainability of GNNs

giza-pp

GIZA++ is a statistical machine translation toolkit that is used to train IBM Models 1-5 and an HMM word alignment model. This package also contains the source for the mkcls tool which generates the word classes necessary for training some of the alignment models.

knowledge_graph_attention_network

KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019

liucsthu/knowledge_graph_attention_network

KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019

liucsthu/awesome-graph-explainability-papers

Papers about explainability of GNNs

liucsthu/Awesome-medical-coding-NLP

A collection of papers in automated medical coding from free-texts :)

liucsthu/Awesome-Neural-Logic

Awesome Neural Logic and Causality: MLN, NLRL, NLM, etc. 因果推断，神经逻辑，强人工智能逻辑推理前沿领域。

liucsthu/awesome-papers-fewshot

Collection for Few-shot Learning

liucsthu/Bert-Multi-Label-Text-Classification

This repo contains a PyTorch implementation of a pretrained BERT model for multi-label text classification.

liucsthu/CADA-VAE-PyTorch

Pytorch implementation of the paper "Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders" (CVPR 2019)

liucsthu/causal-text-papers

Curated research at the intersection of causal inference and natural language processing.

liucsthu/CausalHTP

The official PyTorch code implementation of "Human Trajectory Prediction via Counterfactual Analysis" in ICCV 2021.

liucsthu/ChatPaper

Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文总结+润色+审稿+审稿回复

liucsthu/CL4nlp-dm

Contrastive learning for natural language processing & data mining

liucsthu/Contrastive-Learning-NLP-Papers

liucsthu/COVID-19-TweetIDs

The repository contains an ongoing collection of tweets IDs associated with the novel coronavirus COVID-19 (SARS-CoV-2), which commenced on January 28, 2020.

liucsthu/COVID-Dialogue

liucsthu/D3.js-Demos

liucsthu/DeepEye-APIs

APIs of DeepEye: DeepEye: Towards Automatic Data Visualization [ICDE 2018]

liucsthu/graph-adversarial-learning-literature

A curated list of adversarial attacks and defenses papers on graph-structured data.

liucsthu/graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

liucsthu/gzsl_text

Code for Generalized Zero-Shot Text Classification for ICD Coding (IJCAI 2020)

liucsthu/hello-algorithm

🙈🙉🙊 本项目包括：1、我写的三十万字图解算法题典 2、100 张 IT 相关超清思维导图 3、100 篇大厂面经汇总 4、各语言编程电子书 100 本 5、English version supported !!! 🚀🚀 国人项目上榜首不易，右上角助力一波！干就对了，奥利给 ！🚀🚀

liucsthu/LAAT

A Label Attention Model for ICD Coding from Clinical Text

liucsthu/LGN

A Lexicon-based Graph Neural Network for Chinese NER.

liucsthu/linear_graph_autoencoders

Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R. Hennequin, M. Vazirgiannis) + k-core framework implementation from IJCAI 2019 article "A Degeneracy Framework for Scalable Graph Autoencoders" (G. Salha, R. Hennequin, V.A. Tran, M. Vazirgiannis)

liucsthu/liucsthu.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

liucsthu/Multi-Filter-Residual-Convolutional-Neural-Network

Multi-Filter Residual Convolutional Neural Network for Text Classification

liucsthu/NeuralNLP-NeuralClassifier

An Open-source Neural Hierarchical Multi-label Text Classification Toolkit

liucsthu/poincare-embedding-icd-coding-pytorch

pytorch implementation of poincare embedding for ICD coding hierarchy(ICD-9-CM3)

liucsthu/Self-paced-Contrastive-Learning

Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels for neurips 2021

liucsthu/semi-vae

Re-implementation for paper 'Semi-supervised learning with deep generative models' using lasagne. There is no guarantee for bug free.

liucsthu/vampire

Variational Methods for Pretraining in Resource-limited Environments