Results 181 to 190 of about 110,596 (265)

Fusing Direct and Indirect Measurements Through Multi‐Fidelity Learning For Accelerated Electrocaloric Materials Discovery

Advanced Science, EarlyView.
A multi‐fidelity framework integrates sparse direct and abundant indirect electrocaloric measurements. Multi‐objective active learning accelerates BaTiO3‐based electrocaloric materials discovery at –70∘C$^{\circ }{\rm C}$. A diffuse transition enables an electrocaloric strength of 0.06×$\times$10−6 Km/V at –70℃ with an operational temperature span of ...
Bo Wang, Pengfei Dang, Yuan Tian, Zhengwang He, Wei Gu, Lixue Zhang, Turab Lookman, Yumei Zhou, Dezhen Xue   +8 more
wiley   +1 more source

Comparative hyperparameter optimization of object detection models for precision monitoring of cucumber beetles and similar insects on yellow sticky cards. [PDF]

Sci Rep
Mafuwe K, Dulam RVS, Kambhamettu C, Crossley MS.   +3 more
europepmc   +1 more source

A Bioinspired, Multimodal Soft Tactile Skin with Task‐Adaptive Perception for Intelligent Robotic Manipulation

Advanced Science, EarlyView.
Perception in robotic manipulation improves through the cooperative and complementary operation of biologically inspired multimodal tactile sensors. Receptor‐specific contribution analysis identifies which sensing modalities are required for specific tactile tasks.
Yu‐Jin Lee, Hyeonung Kang, Ju Yeon Woo, Daekyum Kim, Chang‐Soo Han   +4 more
wiley   +1 more source

Enhancing Road Sensor Data Fidelity via FMD Decomposition for Accurate Traffic Flow Prediction Using EBWO-Optimized LGC-BiGRU. [PDF]

Sensors (Basel)
Jiang J, Feofilova A, Topilin I, Beskopylny N.   +3 more
europepmc   +1 more source

Comparison of Approximate Methods for Handling Hyperparameters

I examine two approximate methods for computational implementation of Bayesian hierarchical models, that is, models which include unknown hyperparameters such as regularization constants and noise levels.
David J.C. MacKay
core  

A Site‐Aware Representation Learning Framework For Unified Molecular Interaction Modeling and Generative Design

Advanced Science, EarlyView.
MolDBG is a site‐aware, sequence‐only framework that unifies drug‐target affinity prediction, binding‐site identification, and affinity‐conditioned molecular generation for structured proteins. Guided by multi‐task binding‐site supervision, it aligns interaction‐critical residues before learning drug‐target representations and simultaneously infers ...
Gang Luo, Qianqian Zhang, Chenhao Wang, Zhiheng Yi, Alex Jinpeng Wang, Jing Tang, Min Li   +6 more
wiley   +1 more source

Human-like AI-based auto-field-in-field whole-brain radiotherapy treatment planning with conversation large language model feedback. [PDF]

J Appl Clin Med Phys
Jafar A, Qin A, Atkins G, Hu X, Gao Y, Jia X.   +5 more
europepmc   +1 more source

STWave: Fine‐Scale Spatial Structure Discovery in Microscopic‐Resolution Spatial Transcriptomics via Patchwise Wavelet Graphs

Advanced Science, EarlyView.
STWave transforms massive microscopic‐resolution spatial transcriptomics into interpretable fine‐scale tissue maps through patch‐wise inference, wavelet‐based multi‐scale encoding, and dual‐domain reconstruction. It reduces noise while preserving weak spatial signals, enabling efficient analysis of 6 40 000 spots of 2.47 GB GPU memory and revealing ...
Tao Jiang, Songming Zhang, Xiaofeng Chen, Xiongtao Xiao, Wenming Cao, Weikai Li, Tong Zhao, Bing Li, Xinyue Xu, Zhongshan Li   +9 more
wiley   +1 more source

Prediction model for compressive strength of alkali-activated multi-source solid-waste grouting materials based on generative adversarial networks and machine learning. [PDF]

PLoS One
Yue Q, Yu G, Yao Y, Yang Z, Li Y, Bai L, Xiong G.   +6 more
europepmc   +1 more source

Universal Battery Capacity Degradation Forecasting Driven by Foundation Models Across Diverse Chemistries and Conditions

Advanced Science, EarlyView.
A unified time‐series forecasting framework learns transferable battery capacity‐degradation patterns from 20 heterogeneous datasets spanning chemistries, formats, temperatures, and cycling conditions. A single model delivers competitive predictions on both known and previously unseen datasets, while physics‐guided representation learning improves ...
Joey Chan, Huan Wang, Zhen Chen, Haoyu Pan, Wei Wu, Zirong Wang, Ershun Pan, Min Xie, Lifeng Xi   +8 more
wiley   +1 more source