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Zifeng's Projects

acnet icon acnet

ACNet: Attention Complementary Network for RGBD semantic segmentation

biobridge icon biobridge

ICLR'24 | BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs

construction-site-segmentation icon construction-site-segmentation

An open dataset for semantic segmentation on construction site, released by the paper: "Deep Semantic Segmentation for Visual Understanding on Construction Sites".

cuda_tutorial icon cuda_tutorial

My CUDA C practices while learning the CUDA C Programming Introduction.

cvib-rec icon cvib-rec

Official Implementation of Information Theoretic Counterfactual Learning from Missing Not At Random Feedback. NeurIPS 2020.

deepctr-torch icon deepctr-torch

【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

face_recognition icon face_recognition

A demo on face detection, classification and verification via tensorflow.

gan icon gan

Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN

genres icon genres

Evaluate Generative Relation Extraction

googlescholarmap icon googlescholarmap

A collection of Python scripts that generates a scholar's impact chart and helps create a map of countries from which the scholar is cited

graph4nlp icon graph4nlp

Graph4nlp is the library for the easy use of Graph Neural Networks for NLP. Welcome to visit our DLG4NLP website (https://dlg4nlp.github.io/index.html) for various learning resources!

interacte icon interacte

AAAI 2020 - InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions

learning_from_data icon learning_from_data

The homework of the course Learning From Data taught by Prof.HUANG in Tsinghua-Berkeley Shenzhen Institute(TBSI).

markdown4zhihu icon markdown4zhihu

一键解决知乎导入Markdown文件时图片和公式等问题。

medclip icon medclip

EMNLP'22 | MedCLIP: Contrastive Learning from Unpaired Medical Images and Texts

meditab icon meditab

The code for the paper "MediTab: Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement"

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