[NeurIPS-2023] Annual Conference on Neural Information Processing Systems

Python - 100天从新手到大师

notes of machine learning algorithm derivation

[NeurIPS 2023] MotionGPT: Human Motion as a Foreign Language, a unified motion-language generation model using LLMs

An awesome repository & A comprehensive survey on interpretability of LLM attention heads.

"Deep Generative Modeling": Introductory Examples

Implementation of Statistical Learning Method, Second Edition.《统计学习方法》第二版，算法实现。

A Comprehensive Assessment of Trustworthiness in GPT Models

Official repo to reproduce the paper "How to Backdoor Diffusion Models?" published at CVPR 2023

A curated list of awesome computer vision resources

PyTorch implementation of adversarial attacks [torchattacks]

SLAR (Symmetric Linear Adversarial Robustness game)

Real-time face swap for PC streaming or video calls

PyTorch DDPM implementation

[ECCV2022] Official Implementation of paper "V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer"

The open-sourced Python toolbox for backdoor attacks and defenses.

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

The official code repository for examples in the O'Reilly book 'Generative Deep Learning'

The official code repository for the second edition of the O'Reilly book Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play.

AREFR(Adversarial Robustness Evaluation for Face Recognition) 人脸识别对抗鲁棒性评估平台

This repository contains the ViewFool and ImageNet-V proposed by the paper “ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints” (NeurIPS2022).

Use ChatGPT (or other backends) to generate PPT automatically, all in one single file.

Reverse engineered ChatGPT API

This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.

A tinystruct-based chat module which integrated with @OpenAI GPT-4 / 3.5-turbo / ChatGPT. @tinystruct

This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.

Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"