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 ...
IEEE

Enhancing SEEG-Based Speech Decoding via Convolutional Encoder-Decoder and Scale-Recursive Reconstructor

Abstract: A brain-computer interface (BCI) that decodes speech directly from neural activity provides a rapid and natural means of communication for individuals with speech impairments or aphasia.
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 ...