[UNMAINTAINED] 非监督特征学习与深度学习中文教程，该版本翻译自新版 UFLDL Tutorial 。建议新人们去学习斯坦福的CS231n课程，该门课程在网易云课堂上也有一个配有中文字幕的版本。

Finding Direction of arrival (DOA) of small UAVs using Sparse Denoising Autoencoders and Deep Neural Networks.

For OpenMOSS Mechanistic Interpretability Team's Sparse Autoencoder (SAE) research.

Medical Imaging, Denoising Autoencoder, Sparse Denoising Autoencoder (SDAE) End-to-end and Layer Wise Pretraining

Sparse Autoencoders using FashionMNIST dataset

Code for the paper: Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV 2024.

Hyperspectral Band Selection using Self-Representation Learning with Sparse 1D-Operational Autoencoder (SRL-SOA)

Diagnóstico de falla de rodamiento utilizando descomposición modal empírica y deep learning

Providing the answer to "How to do patching on all available SAEs on GPT-2?". It is an official repository of the implementation of the paper "Evaluating Open-Source Sparse Autoencoders on Disentangling Factual Knowledge in GPT-2 Small"

Use evolution with sparse autoencoders

A framework for conducting interpretability research and for developing an LLM from a synthetic dataset.

Folder contains implementation of Multi layer feed forward networks, Autoencoders, Sparse Autoencoders and many..

Presentation about Autoencoders for Seoul AI Meetup on July 8, 2017.

This repository is created as part of Neural Networks and Deep Learning course at my college. This repo contains the implementations of Neural Network and Deep Learning algorithms.