scutfrank's starred repositories
mahjong-helper
日本麻将助手:牌效+防守+记牌(支持雀魂、天凤)
classifier-balancing
This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020
Revisiting_Deep_Metric_Learning_PyTorch
(ICML 2020) This repo contains code for our paper "Revisiting Training Strategies and Generalization Performance in Deep Metric Learning" (https://arxiv.org/abs/2002.08473) to facilitate consistent research in the field of Deep Metric Learning.
align_uniform
Open source code for paper "Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere" ICML 2020
gpt_academic
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, moss等。
Angular-Penalty-Softmax-Losses-Pytorch
Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)
targeted-supcon
A PyTorch implementation of the paper Targeted Supervised Contrastive Learning for Long-tailed Recognition
Generalized-Long-Tailed-Benchmarks.pytorch
[ECCV 2022] A generalized long-tailed challenge that incorporates both the conventional class-wise imbalance and the overlooked attribute-wise imbalance within each class. The proposed IFL together with other baselines are also included.
Balanced-Contrastive-Learning
Code Release for “Balanced Contrastive Learning for Long-Tailed Visual Recognition”
ViT-pytorch
Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)
WaveletAttention
Wavelet-Attention CNN for Image Classification
ACE_TCAV_Pytorch
Automatic Concept Extraction and TCAV Implemented in Pytorch
Visual-Reasoning-eXplanation
[CVPR 2021] A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts
awesome-xai
Papers about Explainable AI (Deep Learning-based)
Label-Free-XAI
This repository contains the implementation of Label-Free XAI, a new framework to adapt explanation methods to unsupervised models. For more details, please read our ICML 2022 paper: 'Label-Free Explainability for Unsupervised Models'.