IEEE transactions on neural networks and learning systems
Jan 5, 2022
Visual commonsense knowledge has received growing attention in the reasoning of long-tailed visual relationships biased in terms of object and relation labels. Most current methods typically collect and utilize external knowledge for visual relations...
Computational intelligence and neuroscience
Dec 28, 2021
In the past, most of the entity prediction methods based on embedding lacked the training of local core relationships, resulting in a deficiency in the end-to-end training. Aiming at this problem, we propose an end-to-end knowledge graph embedding re...
Journal of medical ethics
Dec 14, 2021
In this paper, we first classify different types of second opinions and evaluate the ethical and epistemological implications of providing those in a clinical context. Second, we discuss the issue of how artificial intelligent (AI) could replace the ...
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Dec 13, 2021
We survey and reflect on how learning (in the form of individual learning and/or culture) can augment evolutionary approaches to the joint optimization of the body and control of a robot. We focus on a class of applications where the goal is to evolv...
Nature communications
Nov 22, 2021
Prediction of drug-target interactions (DTI) plays a vital role in drug development in various areas, such as virtual screening, drug repurposing and identification of potential drug side effects. Despite extensive efforts have been invested in perfe...
Neural networks : the official journal of the International Neural Network Society
Nov 15, 2021
Multi-view learning aims to fully exploit the view-consistency and view-discrepancy for performance improvement. Knowledge Distillation (KD), characterized by the so-called "Teacher-Student" (T-S) learning framework, can transfer information learned ...
Journal of medical systems
Oct 22, 2021
Autonomous intelligent systems are starting to influence clinical practice, as ways to both readily exploit experts' knowledge when contextual conditions demand so, and harness the overwhelming amount of patient related data currently at clinicians' ...
Neural networks : the official journal of the International Neural Network Society
Oct 5, 2021
Spiking Neural Networks (SNNs) have recently emerged as a new generation of low-power deep neural networks due to sparse, asynchronous, and binary event-driven processing. Most previous deep SNN optimization methods focus on static datasets (e.g., MN...
BMC bioinformatics
Oct 4, 2021
BACKGROUND: Blood cancers (BCs) are responsible for over 720 K yearly deaths worldwide. Their prevalence and mortality-rate uphold the relevance of research related to BCs. Despite the availability of different resources establishing Disease-Disease ...
Computational intelligence and neuroscience
Sep 23, 2021
The purpose of knowledge graph entity disambiguation is to match the ambiguous entities to the corresponding entities in the knowledge graph. Current entity ambiguity elimination methods usually use the context information of the entity and its attri...