Results 111 to 120 of about 153,200 (241)

AutomataGPT: Transformer‐Based Forecasting and Ruleset Inference for Two‐Dimensional Cellular Automata

open access: yesAdvanced Science, EarlyView.
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich   +2 more
wiley   +1 more source

Hierarchical Summary Statistics Encoding Across Primary Visual and Posterior Parietal Cortices

open access: yesAdvanced Science, EarlyView.
This study shows that mouse V1 simultaneously encodes the ensemble mean and variance of motion, providing a robust summary‐statistic representation that persists despite single‐neuron variability. These signals propagate to PPC, where they are transformed into abstract category representations during decision making.
Young‐Beom Lee   +4 more
wiley   +1 more source

Evaluating the Utilities of Foundation Models in Single‐Cell Data Analysis

open access: yesAdvanced Science, EarlyView.
This study delivers the first systematic, task‐level evaluation of single‐cell foundation models across eight core analytical tasks. By benchmarking 10 leading models with the scEval framework, it reveals where foundation models truly add value, where task‐specific methods still dominate, and provides concrete, reproducible guidelines to steer the next
Tianyu Liu   +4 more
wiley   +1 more source

An Artificial Antibody‐Based Toolbox Accelerates Validation of Hidden Microproteins Encoded by the Dark Genome

open access: yesAdvanced Science, EarlyView.
Microproteins are hidden treasures encoded by the “dark proteome” but remain largely underexplored due to the lack of highly efficient tools. We developed a molecularly imprinted polymers (MIPs)‐based toolbox (CLAIMID) to achieve accelerated and ultrasensitive microproteins validation at multiple biological scales (single living cells, cell populations,
Hui He   +10 more
wiley   +1 more source

Helix Alignment, Chevrons, and Edge Dislocations in Twist‐Bend Ferroelectric Nematics

open access: yesAdvanced Science, EarlyView.
The recently discovered twist‐bend ferroelectric nematic (NTBF) is the new member of the multiferroic family, representing a fluid with an oblique helicoidal (heliconical) periodic structure of spontaneous electric polarization. The work presents a thorough exploration of the material properties of this phase, how the periodic modulation of ...
Bijaya Basnet   +8 more
wiley   +1 more source

De Novo Multi‐Mechanism Antimicrobial Peptide Design via Multimodal Deep Learning

open access: yesAdvanced Science, EarlyView.
Current AI‐driven peptide discovery often overlooks complex structural data. This study presents M3‐CAD, a generative pipeline that leverages 3D voxel coloring and a massive database of over 12 000 peptides to capture nuanced physicochemical contexts.
Xiaojuan Li   +23 more
wiley   +1 more source

MSMGE-CNN: a multi-scale multi-graph embedding convolutional neural network for motor related EEG decoding

open access: yesMachine Learning: Science and Technology
Deep learning technique has been widely used for decoding motor related electroencephalography (EEG) signals, which has considerably driven the development of motor related brain–computer interfaces (BCIs).
Binren Wang   +6 more
doaj   +1 more source

Deep Learning‐Powered Scalable Cancer Organ Chip for Cancer Precision Medicine

open access: yesAdvanced Science, EarlyView.
This scalable, low‐cost Organ Chip platform, made via injection molding, uses capillary pinning for hydrogel confinement and supports versatile tissue coculture and robust imaging. Deep learning enables label‐free, sensitive phenotypic analysis.
Yu‐Chieh Yuan   +24 more
wiley   +1 more source

Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain

open access: yesAdvanced Science, EarlyView.
A new approach uses simple neural networks to create digital twins of brain activity, capturing how different patterns unfold over time. The method generates and recovers key dynamics even from noisy data. When applied to fMRI, it predicts brain signals and reveals distinctive activity patterns across regions and individuals, opening possibilities for ...
Gabriele Di Antonio   +3 more
wiley   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

open access: yesAdvanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown   +3 more
wiley   +1 more source

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