Results 111 to 120 of about 142,397 (310)
Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
iEdgeDTA: integrated edge information and 1D graph convolutional neural networks for binding affinity prediction [PDF]
, 2023 Natchanon Suviriyapaisal +1 more
openalex +1 more source
Anomaly Detection on Graph Time Series
, 2017 In this paper, we use variational recurrent neural network to investigate the anomaly detection problem on graph time series. The temporal correlation is modeled by the combination of recurrent neural network (RNN) and variational inference (VI), while ...
Hsu, Daniel
core
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Advanced Science, EarlyView.Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Diffusion–Model–Driven Discovery of Ferroelectrics for Photocurrent Applications
Advanced Science, EarlyView.We developed a diffusion model–based generative AI and high‐throughput screening framework that accelerates the discovery of photovoltaic ferroelectrics. By coupling AI driven crystal generation with machine learning and DFT screening, we identified Ca3P2 and LiCdP as new ferroelectric materials exhibiting strong polarization, feasible switching ...
Byung Chul Yeo +3 more
wiley +1 more source
Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare
Advanced Science, EarlyView.Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu +10 more
wiley +1 more source
康复学报ObjectiveTo evaluate the decoding accuracy and model performance of a graph spatio-temporal convolutional neural network (G-STCNN) in motor intention recognition of stroke patients.MethodsWe developed a novel G-STCNN model by integrating graph ...
XU Hui +5 more
doaj
A Relationship-Aware Feature Update Method for Enhanced Graph-Based Neural Networks
IEEE AccessThis paper presents a novel feature update method that leverages the relationships among batch elements, addressing scenarios both with and without an external graph.
Conggui Huang
doaj +1 more source
Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES
Advanced Science, EarlyView.In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu +5 more
wiley +1 more source
Quantization in Graph Convolutional Neural Networks
2021 29th European Signal Processing Conference (EUSIPCO), 2021 Saad, Leila Ben +1 more
openaire +2 more sources