Results 191 to 200 of about 8,140,064 (302)

Prediction of Thermomechanical Behavior of Wood-Plastic Composites Using Machine Learning Models: Emphasis on Extreme Learning Machine. [PDF]

Polymers (Basel)
Hua X, Cao Y, Liu B, Yang X, Xu H, Li L, Wu J.   +6 more
europepmc   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Traffic flow prediction based on improved deep extreme learning machine. [PDF]

Sci Rep
Tian X, Wu S, Xing X, Liu H, Gao H, Chen C.   +5 more
europepmc   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Rank-1 Approximation of Inverse Fisher for Natural Policy Gradients in Deep Reinforcement Learning

Publisher Copyright: © 2026, Transactions on Machine Learning Research. All rights reserved.Natural gradients have long been studied in deep reinforcement learning due to their fast convergence properties and covariant weight updates.
Dash, Satya Prakash, Stoican, Radu, Sun, Mingfei, Kaski, Samuel, Huo, Yingxiao   +4 more
core  

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

Advanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao, Yiming Ma, Baihao Shao, Molly M. Stevens   +3 more
wiley   +1 more source

Electric load forecasting based on kernel extreme learning machine optimized by improved sparrow search algorithm. [PDF]

Sci Rep
Zhang D, Xu Y, Li Y.
europepmc   +1 more source

Advances in Extreme Learning Machines.

, 2020
openaire   +2 more sources

Advances and Perspectives in Graphene‐Based Quantum Dots Enabled Neuromorphic Devices

Advanced Science, EarlyView.
Graphene‐based QDs are zero‐dimensional carbon nanomaterials with pronounced quantum confinement and tunable electronic structures. Herein, we summarize their synthesis strategies and functionalization methods, and highlight their functional roles and operating mechanisms in devices, as well as recent advances in neuromorphic electronics. We anticipate
Yulin Zhen, Wei Zeng, Zherui Zhao, JiYu Zhao, Ziyan Huang, Zhuo Chen, Kui Zhou, Guanglong Ding, Su‐Ting Han, Ye Zhou   +9 more
wiley   +1 more source

A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation. [PDF]

Sci Rep
Yao K, Yan X, Mao X, Li M, Li X, Lian Z, Han Y.   +6 more
europepmc   +1 more source