Visual Analytics for Bridging Unlearning and Retrained Models

A collection of projects designed to help developers quickly get started with building deployable applications using the Anthropic API

Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion

Exploring attention weights in transformer-based models with linguistic knowledge.

Starting kit for the NeurIPS 2023 unlearning challenge

This repository contains Python code for the paper "Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning".

A comprehensive toolbox for model inversion attacks and defenses, which is easy to get started.

Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.

Algorithms to recover input data from their gradient signal through a neural network

Breaching privacy in federated learning scenarios for vision and text

GradAttack is a Python library for easy evaluation of privacy risks in public gradients in Federated Learning, as well as corresponding mitigation strategies.

React content transition slider. Awesome Slider is a 60fps, light weight, performant component that renders an animated set of production ready UI general purpose sliders with fullpage transition s…

React component to compare two images with a slider

FE 기술 소식 큐레이션 뉴스레터

📊 Re-usable, easy interface JavaScript chart library based on D3.js

Github mirror of M. Zinkevich's "Rules of Machine Learning" style guide, with extra goodness.

The full minitorch student suite.

A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

The implementation for paper Joint t-SNE for Comparable Projections of Multiple High-Dimensional Datasets.

Uniform Manifold Approximation and Projection

Transformer Explained Visually: Learn How LLM Transformer Models Work with Interactive Visualization

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑‍🔬

Berkeley CS182/282A Designing, Visualizing and Understanding Deep Neural Networks

Existing Literature about Machine Unlearning

An awesome list of papers on privacy attacks against machine learning

[arXiv:2411.10023] "Model Inversion Attacks: A Survey of Approaches and Countermeasures"

[ICLR24 (Spotlight)] "SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation" by Chongyu Fan*, Jiancheng Liu*, Yihua Zhang, Eric Wong, D…

Awesome Machine Unlearning (A Survey of Machine Unlearning)