eLife

Modality-agnostic decoding of vision and language from fMRI

Modality-agnostic decoders leverage modality-invariant representations in human subjects' brain activity to predict stimuli irrespective of their modality (image, text, mental imagery).
Tech Xplore

AI-powered surrogate models bring real-time simulation to composite manufacturing

A recent publication from IMDEA Materials Institute and the Technical University of Madrid (UPM) presents a major step ...
Scientific Research Publishing

Predicting Stock Price Movements Using Deep Learning Techniques ()

Stock Price Prediction, Deep Learning, LSTM, GRU, Attention Mechanism, Financial Time Series Share and Cite: Kirui, D. (2026) ...
Scientific Research Publishing

Malhotra, P., Ramakrishnan, A., Anand, G., Vig, L., Agarwal, P. and Shroff, G. (2016) LSTM-Based Encoder-Decoder for Multi-Sensor Anomaly Detection.

ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...
IEEE

Deep Learning-Based Iterative Residual Encoder-Decoder Solution for Electromagnetic Modeling over a Broad Frequency Band

Abstract: In this letter, we propose a deep learning-based iterative residual encoder-decoder method (IRED), which provides an efficient deep learning framework for electromagnetic modeling over a ...