Awesome Machine Unlearning (A Survey of Machine Unlearning)

A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. TPAMI, 2024.

[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, Dennis Wei, Sijia Liu

[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

RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models. NeurIPS 2024

Continual Forgetting for Pre-trained Vision Models (CVPR 2024)

An implementation of Transformer with Expire-Span, a circuit for learning which memories to retain

Code to reproduce experiments from the paper "Continual Pre-Training Mitigates Forgetting in Language and Vision" https://arxiv.org/abs/2205.09357

[ICML 2023] "Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability"

[ECCV24] "Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning" by Chongyu Fan*, Jiancheng Liu*, Alfred Hero, Sijia Liu

An application helps you remember things before you leave your room by using iBeacons.

[ICML 2023] "Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability"

This is repository contains code for experiment to evaluate catastrophic forgetting in neural networks.

Deletes old tweets, archiving them as json to Dropbox.

An attempt to make a model forget what it has learnt

Personal portfolio- https://shrutijindal674.github.io/

Python3 based script that reminds you of a particular time on a particular day.

This repository is an implementation of Paper "Robust Natural Language Inference Models with Example Forgetting", which studies importance of forgettable example in making robust NLI Models