Autoencoder can learn the structure of data adaptively and represent data efficiently. These properties make autoencoder not only suit huge volume and vari
Then, we build stacked denoising sparse autoencoders which has multi-hidden layers by layer-wisely stacking denoising sparse autoencoders. Experiments are designed to explore the influences of corrupting operation and sparsity constraint on different datasets, using the networks with various depth and ...
Sparse codingStacked autoencodersUnsupervised learningLearning results depend on the representation of data, so how to efficiently represent data has been a research hot spot in machine learning and artificial intelligence. With the deepening of the......
load(path, map_location=sparse_autoencoder.cfg.device) Training a Sparse Autoencoder on a Language Model Sparse Autoencoders can be intimidating at first but it's fairly simple to train one once you know what each part of the config does. I've created a config class which you instantiate...
This library is used to train and evaluate Sparse Autoencoders (SAEs). It handles the following training types: e2e (end-to-end): Loss function includes sparsity and final model kl_divergence. e2e + downstream reconstruction: Loss function includes sparsity, final model kl_divergence, and MSE ...
DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation research areaComputer Vision|conferenceICLRPublished year2025 AuthorsJiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang†‡, Dinghuai Zhang§, Navdeep Jaitly, Josh Susskind, Shuangfei Zhai ...
DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation content typepaper|research areaComputer Vision|conferenceICLRPublished year2025 AuthorsJiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang†‡, Dinghuai Zhang§, Navdeep Jaitly, Josh Susskind, Shuangfei Zhai ...
Our research focused on evaluating different auto-encoders for enhancing network intrusion detection. The proposed method sparse deep denoising auto-encoder ... BA Manjunatha,KA Shastry,Naresh, E.Pareek, Piyush KumarReddy, Kadiri Thirupal - 《Soft Computing A Fusion of Foundations Methodologies & ...
TempFormer: Temporally Consistent Transformer for Video Denoising October 11, 2022 European Conference on Computer Vision (ECCV) (2022) Mingyang Song (ETH Zürich) Yang Zhang (DisneyResearch|Studios) Tunç O. Aydın (DisneyResearch|Studios) Facial Animation with Disentangled Identity and Motion usi...
Geospatial Mechanistic Interpretability of Large Language Models (Read more on arXiv or HuggingFace) Kevin Roitero, Stefano Mizzaro, sdesabbata This paper introduces a framework using spatial analysis and sparse autoencoders to interpret how Large Language Models internally represent geographical information...