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Transformer decoders explained step-by-step from scratch

Transformers have revolutionized deep learning, but have you ever wondered how the decoder in a transformer actually works? In this video, we break down Decoder Architecture in Transformers step by ...
eLife

High-Fidelity Neural Speech Reconstruction through an Efficient Acoustic-Linguistic Dual-Pathway Framework

This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...
Scientific Research Publishing

Applying Deep Learning Techniques for Automated Analysis and Interpretation of Financial Statements ()

Multimodal Learning, Deep Learning, Financial Statement Analysis, LSTM, FinBERT, Financial Text Mining, Automated Interpretation, Financial Analytics Share and Cite: Wandwi, G. and Mbekomize, C. (2025 ...
C&EN

Machine Learning Approaches for Optimizing Drug Combinations in Neurodegenerative Diseases: A Brief Review

You are free to share (copy and redistribute) this article in any medium or format and to adapt (remix, transform, and build upon) the material for any purpose, even commercially within the parameters ...
IEEE

DED-SAM:Adapting Segment Anything Model 2 for Dual Encoder–Decoder Change Detection

Abstract: Change detection has become a crucial topic in the field of remote sensing deep learning due to its extensive application in earth observation. However, real remote sensing images often ...
GitHub

Code Repository for Paper "Pretraining Graph State Encoders for microRTS using Graph Self-Supervised Learning"

You will need to use a Python version between 3.9 (inclusive) and 3.13 (exclusive) to run the scripts and notebooks. We use Poetry to set up our Python environment as ...
IEEE

FreqWave-TranDuD: A Multivariate Time Series Anomaly Detection Method Based on Wavelet and Fourier Transforms

Abstract: Time series anomaly detection (AD) plays a crucial role in network systems. It enables the timely detection of anomalies and root cause analysis, helping to prevent unnecessary losses.