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Official Pytorch implementation of "Learning Debiased Representation via Disentangled Feature Augmentation (Neurips 2021, Oral)"
The offical code of Cooperative and Adversarial Learning: Co-Enhancing Discriminability and Transferability in Domain Adaptation
The implement of "Learning Disentangled Semantic Representation for Domain Adaptation" (IJCAI 2019)
Tensorflow implementation of Disentangling Latent Space for VAE by Label Relevant/Irrelevant Dimensions (CVPR 2019)
为GPT/GLM等LLM大语言模型提供实用化交互接口,特别优化论文阅读/润色/写作体验,模块化设计,支持自定义快捷按钮&函数插件,支持Python和C++等项目剖析&自译解功能,PDF/LaTex论文翻译&总结功能,支持并行问询多种LLM模型,支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…
Recommendation Algorithm大规模推荐算法库,包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM,DSIN,SIGN,IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESM…
chrjabs / Grape-Academic-Theme
Forked from naye0ng/Grape-Theme🍇 Grape-Academic-Theme: A modified version of the Jekyll Grape-Theme for an academic Portfolio. (Can include a blog)
LibAUC: A Deep Learning Library for X-Risk Optimization
This repository contains the code of the distribution shift framework presented in A Fine-Grained Analysis on Distribution Shift (Wiles et al., 2022).
Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
We are building an open database of COVID-19 cases with chest X-ray or CT images.
Moco contrastive unsupervised pretraining on Nih Chest X-Rays dataset.
医学影像数据集列表 『An Index for Medical Imaging Datasets』
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
A TensorFlow Keras implementation of "Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts" (KDD 2018)
A Tensorflow implementation of the paper arXiv:1604.03539
The implementation of focal loss proposed on "Focal Loss for Dense Object Detection" by KM He and support for multi-label dataset.
resource collection for transfer learning!
A collection of AWESOME things about domian adaptation
Go实现的Trojan代理,支持多路复用/路由功能/CDN中转/Shadowsocks混淆插件,多平台,无依赖。A Trojan proxy written in Go. An unidentifiable mechanism that helps you bypass GFW. https://p4gefau1t.github.io/trojan-go/