ERASURE: Redefining Privacy Through Selective Machine Unlearning
Multi-GPU framework for reproducible image-unlearning evaluation, with independent training, unlearning and evaluation seeds and extensible datasets, models, methods and metrics. Published at WIPE-OUT 2 (ECML-PKDD 2026).
Machine Unlearning Framework
This repository is based on Stock Prediction using AAPL-stock-data. Here, we have used Qwen1.5-0.5b model and LSTM model to predict the stock and prepared a compact Machine Unlearning module/methods to act whenever poisoned is getting injected into the dataflow. Therefore, it ensures a accurate prediction of yfinance stock with following trends.
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