Results 71 to 80 of about 3,278,052 (298)

Advanced artificial intelligence in piRNA and PIWI-like protein research: A systematic review of recurrent neural networks, long short-term memory, and emerging computational techniques

Biomédica: revista del Instituto Nacional de Salud
Introduction. PIWI-interacting RNAs are small and non-coding RNAs involved in gene regulation and transposable element repression, emerging as critical biomarkers and therapeutic targets in oncology. Advances in artificial intelligence, such as recurrent
Jheremy Sebastián Reyes, Jhonathan David Guevara, Laura Tatiana Picón, Iris Lorena Sánchez, Libia Andrea Gaona, María Paula Montoya, Luis Eduardo Pino   +6 more
doaj   +1 more source

TOWARDS A SPECTRUM OF GRAPH CONVOLUTIONAL NETWORKS [PDF]

2018 IEEE Data Science Workshop (DSW), 2018
We present our ongoing work on understanding the limitations of graph convolutional networks (GCNs) as well as our work on generalizations of graph convolutions for representing more complex node attribute dependencies. Based on an analysis of GCNs with the help of the corresponding computation graphs, we propose a generalization of existing GCNs where
Mathias Niepert, Alberto García-Durán
openaire   +4 more sources

Relational graph convolutional networks: a closer look

PeerJ Computer Science, 2022
In this article, we describe a reproduction of the Relational Graph Convolutional Network (RGCN). Using our reproduction, we explain the intuition behind the model. Our reproduction results empirically validate the correctness of our implementations using benchmark Knowledge Graph datasets on node classification and link prediction
Thiviyan Thanapalasingam, Lucas van Berkel, Peter Bloem, Paul Groth   +3 more
openaire   +9 more sources

Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning

, 2021
Graph-based Semi-Supervised Learning (SSL) aims to transfer the labels of a handful of labeled data to the remaining massive unlabeled data via a graph.
Wan, Sheng, Yang, Jian, Gong, Chen, Pan, Shirui   +3 more
core  

On‐Chip Photonic Neural Network Architectures

Advanced Optical Materials, EarlyView.
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong, Berkay Neseli, Seungyeon Cho, Seungsoo Lee, Yeonjun Kim, Seungyoon Choi, Hyo‐Hoon Park, Hamza Kurt   +7 more
wiley   +1 more source

Scalable Graph Convolutional Networks With Fast Localized Spectral Filter for Directed Graphs

IEEE Access, 2020
Graph convolutional neural netwoks (GCNNs) have been emerged to handle graph-structured data in recent years. Most existing GCNNs are either spatial approaches working on neighborhood of each node, or spectral approaches based on graph Laplacian ...
Chensheng Li, Xiaowei Qin, Xiaodong Xu, Dujia Yang, Guo Wei   +4 more
doaj   +1 more source

Modeling Physico-Chemical ADMET Endpoints With Multitask Graph Convolutional Networks [PDF]

, 2019
Simple physico-chemical properties like logD, solubility or serum albumin binding have a direct impact on the likelihood of success of compounds in clinical trials.
Floriane, Montanari, Djork-Arné, Clevert, Antonius, ter Laak, Lara, Kuhnke   +3 more
core   +1 more source

Graph Neural Networks with Convolutional ARMA Filters

, 2022
Popular graph neural networks implement convolution operations on graphs based on polynomial spectral filters. In this paper, we propose a novel graph convolutional layer inspired by the auto-regressive moving average (ARMA) filter that, compared to ...
Alippi C., Livi L., Grattarola D., Bianchi F. M.   +3 more
core   +1 more source

Multimodal Engagement Assessment in Children During Invented Story Paradigm With a Social Robot

Advanced Robotics Research, EarlyView.
A multimodal framework is proposed to assess children's engagement during storytelling interactions with a social robot. Gaze, physiological, and behavioral data are combined and validated against observer ratings. An automated gaze‐labeling strategy is introduced, and supervised classifiers achieve high accuracy. The study supports scalable engagement
Laura Fiorini, Elena Adelucci, Stefano Scatigna, Lorenzo Pugi, Alice Bruni, Benedetta Carotenuto, Chiara Pecini, Filippo Cavallo   +7 more
wiley   +1 more source

Empowering Simple Graph Convolutional Networks [PDF]

Many neural networks for graphs are based on the graph convolution (GC) operator, proposed more than a decade ago. Since then, many alternative definitions have been proposed, which tend to add complexity (and nonlinearity) to the model.
Pasa, L, Navarin, N, Sperduti, A, Erb, W
core   +1 more source