There are 0 repository under sparse-autoencoders topic.
[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。
For OpenMOSS Mechanistic Interpretability Team's Sparse Autoencoder (SAE) research.
Finding Direction of arrival (DOA) of small UAVs using Sparse Denoising Autoencoders and Deep Neural Networks.
Medical Imaging, Denoising Autoencoder, Sparse Denoising Autoencoder (SDAE) End-to-end and Layer Wise Pretraining
Hypothesizing interpretable relationships in text datasets using sparse autoencoders.
Code for the paper: Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV 2024.
Sparse Autoencoders using FashionMNIST dataset
Hyperspectral Band Selection using Self-Representation Learning with Sparse 1D-Operational Autoencoder (SRL-SOA)
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"
A tiny easily hackable implementation of a feature dashboard.
Diagnóstico de falla de rodamiento utilizando descomposición modal empírica y deep learning
Use evolution with sparse autoencoders
Implementation and analysis of Sparse Autoencoders for neural network interpretability research. Features interactive visualization dashboard and W&B integration.
A framework for conducting interpretability research and for developing an LLM from a synthetic dataset.
KAN-LLaMA: An Interpretable Large Language Model With KAN-based Sparse Autoencoders
My AI interpretability research journey
Folder contains implementation of Multi layer feed forward networks, Autoencoders, Sparse Autoencoders and many..
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.
Presentation about Autoencoders for Seoul AI Meetup on July 8, 2017.