IEEE

Pattern-Based Feature Extraction for Improved Deep Learning in Financial Time Series Classification

Abstract: In this paper, the authors introduce a novel feature extraction method based on pattern detection in financial data to enhance the performance of deep learning models for financial time ...
GitHub

Diffusion Transformers with Representation Autoencoders (RAE)

We present Representation Autoencoders (RAE), a class of autoencoders that utilize pretrained, frozen representation encoders such as DINOv2 and SigLIP2 as encoders with trained ViT decoders. RAE can ...
Kotaku

Xbox Series X Is Back in Stock at an All-Time Low for Another Clearance Push, While PlayStation Stays Sold Out

This article is part of Kotaku Deals, produced separately from the editorial team. We may earn a commission when you buy through links on the site. Gamers looking to upgrade their gaming setup for ...
GitHub

SVG: Latent Diffusion Model without Variational Autoencoder

SVG Autoencoder - Uses a frozen representation encoder with a residual branch to compensate the information loss and a learned convolutional decoder to transfer the SVG latent space to pixel space.
IEEE

Online Public Opinion Situation Assessment by Deep Sparse Autoencoder and Time-Series Modeling Convolutional Neural Network

Abstract: We have developed an innovative framework for analyzing online public sentiment, referred to as the Online Public Opinion Situation Assessment (OPOSA) model. This model employs Deep Sparse ...