这个作业未来或将是你的开源项目，标题的内容可以来自作业中的核心关键词，让读者一眼看出你所完成的工作/做出的好玩demo
如果暂时未想好，起名时可以参考“太极图形课S1-xxx作业”
如下是作业（项目）展开说明的方法，可以帮大家理清思路，并且也对读者非常友好，请小伙伴们多多参考哦
这里可以简要描述作业（项目）的基本背景情况，它源自哪里？能够有效解决哪些问题？可以尽情列举它的亮点哦
这里可以展示这份作业（项目）run起来后的可视化效果，可以让其他人更直观感受到你的工作
脉络清晰的结构能完整展示你的设计思想，以及实现方式，方便读者快读代入，建议可以在repo的目录中包含如下内容： 这个部分希望大家可以大作业中加入，小作业中可以选择性加入（如果不加也是OK的）
-LICENSE
-|data
-README.MD
-xxx.py
相信读者们看到这里已经迫不及待想尝试了，这里标记好快速上手的方式即可~
例如: python3 main.py
CapsGNN ⠀⠀ A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019). Abstract The high-quality node embeddings learned from the Graph Neur
Beyond ImageNet Attack: Towards Crafting Adversarial Examples for Black-box Domains (ICLR'2022) This is the Pytorch code for our paper Beyond ImageNet
An Open-Source Framework for Prompt-learning. Overview • Installation • How To Use • Docs • Paper • Citation • What's New? Nov 2021: Now we have relea
TorchSeg This project aims at providing a fast, modular reference implementation for semantic segmentation models using PyTorch. Highlights Modular De
multi-task_losses_optimizer Implement the Pareto Optimizer and pcgrad to make a self-adaptive loss for multi-task 已经实验过了，不会有cuda out of memory情况 ##Par
KoDALLE Utilizing pretrained language model’s token embedding layer and position embedding layer as DALLE’s text encoder. Background Training DALLE mo
Learning Generative Models of Textured 3D Meshes from Real-World Images This is the reference implementation of "Learning Generative Models of Texture
RE2 This is a pytorch implementation of the ACL 2019 paper "Simple and Effective Text Matching with Richer Alignment Features". The original Tensorflo
Awesome Machine Learning Jupyter Notebooks for Google Colaboratory A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook
Contents XingGAN or CrossingGAN Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Evaluation Acknowl
Permuton-induced Chinese Restaurant Process Note: Currently only the Matlab version is available, but a Python version will be available soon! This is
Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser Abstract The success of deep denoisers on real-world colo
Score refinement for confidence-based 3D multi-object tracking Our video gives a brief explanation of our Method. This is the official code for the pa
Self Supervised Learning with Fastai Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks. Install pip install self-
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2020
TrackTech: Real-time tracking of subjects and objects on multiple cameras This project is part of the 2021 spring bachelor final project of the Bachel
Towards Long-Form Video Understanding Chao-Yuan Wu, Philipp Krähenbühl, CVPR 2021 [Paper] [Project Page] [Dataset] Citation @inproceedings{lvu2021,
R-Drop: Regularized Dropout for Neural Networks R-drop is a simple yet very effective regularization method built upon dropout, by minimizing the bidi
Couple Learning for SED This repository provides the data and source code for sound event detection (SED) task. The improvement of the Couple Learning
Graph-to-Tree Learning for Solving Math Word Problems PyTorch implementation of Graph based Math Word Problem solver described in our ACL 2020 paper G
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