Representation of external and internal states in the brain plays a critical role in enabling suitable behavior. Recent studies suggest that state representation and state value can be simultaneously learned through Temporal-Difference-Reinforcement-...
Pathological images are prone to artifacts during scanning and preparation, which can compromise diagnostic accuracy. Therefore, robust artifact detection is essential for improving image quality and ensuring reliable pathological assessments. Howeve...
. The accurate assessment of cognitive impairment plays a vital role in more targeted treatments for Dementia. Eye movement analysis is a non-invasive and objective method that offers fine-grained insight into cognitive functioning, complementing con...
To solve the problems of existing encrypted traffic classification methods, such as the need for large-scale training data, high computational costs, and poor generalization ability, an encrypted traffic classification method based on autoencoders an...
The increased popularity of smartphone-based human activity recognition (HAR) in recent decades has been driven by its low computational requirements and user privacy protection. Yet, developing a reliable smartphone-based HAR still presents several ...
Molecular circuits capable of autonomous learning could unlock novel applications in fields such as bioengineering and synthetic biology. To this end, existing chemical implementations of neural computing have primarily relied on emulating discrete-l...
Alterations in brain connectivity provide early indications of neurodegenerative diseases like Alzheimer's disease (AD). Here, we present a novel framework that integrates a Hidden Markov Model (HMM) within the architecture of a convolutional neural ...
Journal of chemical information and modeling
Sep 22, 2025
In this work, we introduce auxiliary discriminator sequence generative adversarial networks (ADSeqGAN), a novel approach for molecular generation in small-sample data sets. Traditional generative models often struggle with limited training data, part...
Journal of chemical information and modeling
Sep 22, 2025
We present TeNNet-SAC (hermodynamics-mbedded eural work for egment ctivity oefficient) model, a novel machine learning framework for predicting activity coefficients in liquid mixtures using only the SMILES representations of the constituent molecule...
Early diagnosis of gastrointestinal (GI) cancer is critical. Raman spectroscopy combined with deep learning offers a noninvasive molecular quantification approach. This study developed a synergistic framework integrating Raman spectroscopy and convol...
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