[NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

Generate 3D objects conditioned on text or images

Code for CVPR22 paper "Deep Unlearning via Randomized Conditionally Independent Hessians"

Unsupervised Image-to-Image Translation with Self-Attention Networks Official PyTorch Implementation (IEEE BigComp 2020, This paper has been accepted as a REGULAR paper presented at IEEE Internatio…

Lime: Explaining the predictions of any machine learning classifier

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

The Official PyTorch Implementation of "VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models" (ICLR 2021 spotlight paper)

[ICML 2023] official implementation for "Input Perturbation Reduces Exposure Bias in Diffusion Models"

Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"

Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

JAX implementation of VQGAN

🦋A PyTorch implementation of BigGAN with pretrained weights and conversion scripts.

The author's officially unofficial PyTorch BigGAN implementation.

Open reproduction of MUSE for fast text2image generation.

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

Repository for the paper "Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images"

Official PyTorch implementation for paper: Diffusion-GAN: Training GANs with Diffusion

Erasing data from machine learning models! ✏️

Awesome Machine Unlearning (A Survey of Machine Unlearning)

ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。

pytorch structural similarity (SSIM) loss

Code related to the paper "Machine Unlearning of Features and Labels"

Implementation of Generating Diverse High-Fidelity Images with VQ-VAE-2 in PyTorch

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

PyTorch implementations of Generative Adversarial Networks.

From Gradient Leakage to Adversarial Attacks in Federated Learning

Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)

A Collection of Variational Autoencoders (VAE) in PyTorch.