Physical chemistry chemical physics : PCCP
Oct 5, 2022
Efficient prediction of the partition coefficient (log ) between polar and non-polar phases could shorten the cycle of drug and materials design. In this work, a descriptor, named 〈 - ACSFs〉, is proposed to take the explicit polarization effects in t...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
This article develops an adaptive observation-based efficient reinforcement learning (RL) approach for systems with uncertain drift dynamics. A novel concurrent learning adaptive extended observer (CL-AEO) is first designed to jointly estimate the sy...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
Training neural networks with backpropagation (BP) requires a sequential passing of activations and gradients. This has been recognized as the lockings (i.e., the forward, backward, and update lockings) among modules (each module contains a stack of ...
Computational intelligence and neuroscience
Oct 5, 2022
In recent years, numerous studies have successfully implemented machine learning strategies in a wide range of application areas. Therefore, several different deep learning models exist, each one tailored to a certain software task. Using deep learni...
Computers in biology and medicine
Oct 4, 2022
AIM OF STUDY: Glioblastoma Multiforme (GBM) is an aggressive brain cancer in adults that kills most patients in the first year due to ineffective treatment. Different clinical, biomedical, and image data features are needed to analyze GBM, increasing...
IEEE transactions on pattern analysis and machine intelligence
Oct 4, 2022
Exabytes of data are generated daily by humans, leading to the growing needs for new efforts in dealing with the grand challenges for multi-label learning brought by big data. For example, extreme multi-label classification is an active and rapidly g...
IEEE transactions on pattern analysis and machine intelligence
Oct 4, 2022
Spiking neural networks (SNNs) have shown clear advantages over traditional artificial neural networks (ANNs) for low latency and high computational efficiency, due to their event-driven nature and sparse communication. However, the training of deep ...
IEEE transactions on pattern analysis and machine intelligence
Oct 4, 2022
Conventional machine learning algorithms suffer the problem that the model trained on existing data fails to generalize well to the data sampled from other distributions. To tackle this issue, unsupervised domain adaptation (UDA) transfers the knowle...
IEEE transactions on pattern analysis and machine intelligence
Oct 4, 2022
Classification of 3D objects - the selection of a category in which each object belongs - is of great interest in the field of machine learning. Numerous researchers use deep neural networks to address this problem, altering the network architecture ...
ACS sensors
Oct 4, 2022
Utilizing smart face masks to monitor and analyze respiratory signals is a convenient and effective method to give an early warning for chronic respiratory diseases. In this work, a smart face mask is proposed with an air-permeable and biodegradable ...