Results 151 to 160 of about 150,984 (329)

Engineered Living Systems With Self‐Organizing Neural Networks: From Anatomy to Behavior and Gene Expression

open access: yesAdvanced Science, EarlyView.
Ectodermal tissue excised from Xenopus embryos self‐organizes into a three‐dimensional mucociliary organoid. Here, we generate a neural variant, termed neurobot, by implanting neural precursor cells. Neurobots develop mature neurons, adopt distinct morphologies, exhibit more complex motility, and respond differentially to neuroactive compounds. Imaging
Haleh Fotowat   +6 more
wiley   +1 more source

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

Knowledge Discovery through Symbolic Regression with HeuristicLab [PDF]

open access: bronze, 2012
Gabriel Kronberger   +5 more
openalex   +1 more source

rWTC‐MBTA Vaccine, Alone and Enhanced with Anti‐PD1, Elicits Immune Responses against CNS and Peripheral B‐Cell Lymphoma

open access: yesAdvanced Science, EarlyView.
An autologous whole‐tumor‐cell vaccine (rWTC‐MBTA) is evaluated in murine CNS lymphoma. Subcutaneous vaccination activates dendritic cells, broadens T‐cell priming, and drives lymphocyte trafficking to brain tumors, producing durable tumor control. Longitudinal bioluminescence and adoptive‐transfer assays verify CNS engagement. Combination with anti‐PD‐
Yaping Zhang   +10 more
wiley   +1 more source

Diffusion-Based Symbolic Regression

open access: yes
Diffusion has emerged as a powerful framework for generative modeling, achieving remarkable success in applications such as image and audio synthesis. Enlightened by this progress, we propose a novel diffusion-based approach for symbolic regression. We construct a random mask-based diffusion and denoising process to generate diverse and high-quality ...
Bastiani, Zachary   +3 more
openaire   +2 more sources

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

Development of interpretable, data-driven plasticity models with symbolic regression

open access: green, 2021
Geoffrey Bomarito   +5 more
openalex   +2 more sources

Memetic semantic boosting for symbolic regression

open access: yesGenetic Programming and Evolvable Machines
Abstract This paper introduces a novel approach called semantic boosting regression (SBR), leveraging the principles of boosting algorithms in symbolic regression using a Memetic Semantic GP for Symbolic Regression (MSGP) algorithm as weak learners.
Leite, Alessandro, Schoenauer, Marc
openaire   +1 more source

Endocytic Control of Cell‐Autonomous and Non‐Cell‐Autonomous Functions of p53

open access: yesAdvanced Science, EarlyView.
NUMB Ex3‐containing isoforms localize to the plasma membrane, where they recruit p53 through SNX9 and direct it to multivesicular bodies and exosomes. Exported p53 is taken up by neighboring cells and activates nuclear programs, revealing an intercellular, exosome‐based pathway that might help establish a tumor‐suppressive microenvironment.
Roberta Cacciatore   +20 more
wiley   +1 more source

SymbolNet: neural symbolic regression with adaptive dynamic pruning for compression

open access: yesMachine Learning: Science and Technology
Compact symbolic expressions have been shown to be more efficient than neural network (NN) models in terms of resource consumption and inference speed when implemented on custom hardware such as field-programmable gate arrays (FPGAs), while maintaining ...
Ho Fung Tsoi   +3 more
doaj   +1 more source

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