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Scientific Research Publishing

Machine Learning for Financial Risk Management: Modeling Time-Varying Factor Sensitivities Using Factor Variational Autoencoders ()

Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.
Science Daily

AI just found 5 powerful materials that could replace lithium batteries

AI is helping scientists crack the code on next-gen batteries that could replace lithium-ion tech. By discovering novel porous materials, researchers may have paved the way for more powerful and ...
GitHub

Enhancing EV Cost Prediction Using AutoEncoder-Based Feature Learning

Electric Vehicle (EV) cost prediction involves analyzing complex, high-dimensional data that often contains noise, multicollinearity, and irrelevant features. Traditional regression models struggle to ...
C&EN

Noise-Consistent Hypergraph Autoencoder Based on Contrastive Learning for Cancer ceRNA Association Prediction in Complex Biological Regulatory Networks

Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun 130012, China ...
GitHub

TorchScript based ONNX exporter: Shape Inference failure

I want to export the AutoencoderKLCosmos model to ONNX using the TorchScript-based exporter. I'm using the script below import torch from diffusers.models import AutoencoderKLCosmos dtype = ...
IEEE

Autoencoder-Based Discriminant Locality-Preserving Projections for Fault Diagnosis

Abstract: In complex industrial production environments, the efficacy of fault diagnostic techniques has become increasingly important and can enhance the reliability and safety of systems. In recent ...
IEEE

Deep Learning-Based Coseismic Deformation Estimation From InSAR Interferograms

Abstract: Accurate automated extraction of coseismic deformation from synthetic aperture radar (SAR) data can be challenging owing to interference from inherent atmospheric noise. Particularly, the ...