Results 131 to 140 of about 38,367 (259)

SPADE: A Deep Learning Framework for Spatial Mapping and Quantitative Cell–Cell Interaction Inference

open access: yesAdvanced Science, EarlyView.
SPADE integrates spatial transcriptomics with single‐cell RNA sequencing by using cell–cell communications (CCC) as a guide for spatial mapping. It improves cell‐type localization, enhances sparse gene‐expression signals, and reveals CCC programs at single‐spot resolution.
Xinyi Li, Ning Zhang, Zijie Jin
wiley   +1 more source

Brain‐Computer Interface Training Fosters Perceptual Skills to Detect Errors

open access: yesAdvanced Science, EarlyView.
Accurate perception of visuomotor errors underpins motor precision and learning, yet conventional behavioral training fails to improve sensitivity to subtle errors. Real‐time EEG‐based brain‐computer interface feedback targeting the error positivity component enhances perceptual learning of small errors.
Deland H. Liu   +4 more
wiley   +1 more source

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

open access: yesAdvanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang   +11 more
wiley   +1 more source

Correcting Apparent Priming Bias Unveils Fertilizer Nitrogen‐Risk Archetypes of Surplus and Depletion Across Asian Rice Systems

open access: yesAdvanced Science, EarlyView.
Correcting the apparent priming effect resolves systematic biases in Asian rice fertilizer nitrogen accounting. Net soil retention drops below 7%, while 48% of fertilizer escapes, inflicting US$98.53 billion in annual reactive‐nitrogen damages. High‐resolution mapping uncovers N‐risk archetypes across 42% of the rice area, delivering a spatially ...
Xiuyun Liu   +5 more
wiley   +1 more source

Sustainable Hyperparameter Optimization

open access: yes
https://www.ieeesmc.org/cai-2026/tutorial-7-sustainable-hyperparameter-optimization/ https://github.com/ai-for-decision-making-tue ...
AMINI, Sasan, Bliek, Laurens
openaire   +2 more sources

Hyperparameter Optimization of Convolutional Neural Networks for Robust Tumor Image Classification. [PDF]

open access: yesDiagnostics (Basel)
Hussain SM   +4 more
europepmc   +1 more source

A Versatile‐Designable Framework for Active and Programmable Shape‐Morphing Soft Matter Systems: From Inverse Design to Closed‐Loop Control

open access: yesAdvanced Science, EarlyView.
A versatile framework integrates addressable electrothermal actuation and strain‐constraint mechanisms to construct programmable shape‐morphing soft matter systems. By combining an analytical inverse design strategy for high‐fidelity 3D surface reconstruction with deep learning‐based closed‐loop control, this approach enables zero‐energy shape locking,
Kai Liu   +5 more
wiley   +1 more source

A flexible framework for hyperparameter optimization using homotopy and surrogate models. [PDF]

open access: yesSci Rep
Abraham SJ   +5 more
europepmc   +1 more source

Hyperparameter optimization for cardiovascular disease data-driven prognostic system. [PDF]

open access: yesVis Comput Ind Biomed Art, 2023
Saputra J   +3 more
europepmc   +1 more source

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