Fully implicit parallel simulation of single neurons

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Gels made of telechelic polymers connected by reversible cross-linkers are a versatile design platform for biocompatible viscoelastic materials. Their linear response to a step strain displays a fast, near-exponential relaxation when using low-valence cros ...

Many empirical studies have provided evidence for the emergence of algorithmic mechanisms (abilities) in the learning of language models, that lead to qualitative improvements in the model capabilities. Yet, a theoretical characterization of how such mecha ...

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

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Contemporary AI faces important limitations that remain unresolved despite significant successes. Chief among these are the inability to acquire new knowledge without destroying old, the incomprehensible and nonengineerable nature of internal representatio ...

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The outstanding information processing capacity of the brain relies on numerous molecular mechanisms. It is an extremely energy-expensive function, which involves specialization and collaboration of different cell types. A common framework to study the com ...

Rigid body interactions are fundamental to numerous scientific disciplines, but remain challenging to simulate due to their abrupt nonlinear nature and sensitivity to complex, often unknown environmental factors. These challenges call for adaptable learnin ...

Fully implicit parallel simulation of single neurons

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Valence can control the nonexponential viscoelastic relaxation of multivalent reversible gels

A phase transition between positional and semantic learning in a solvable model of dot-product attention

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Generalized Bradley-Terry Models for Score Estimation from Paired Comparisons

Posterior-Based Analysis of Spatio-Temporal Features for Sign Language Assessment

Characterization of Transverse Instabilities Driven by Electron Cloud

Strong gravitational lensing's 'external shear' is not shear

Simulating Interacting Quantum Systems with Near-Term Quantum Computers

Training hybrid neural networks with multimode optical nonlinearities using digital twins

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Accelerating Spectral Clustering under Fairness Constraints

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Principles of Network Plasticity in Neocortical Microcircuits

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Foundations of a New Learning Paradigm in AI Grounded in the Principles of Evolutionary Developmental Biology

Defining myocardial fiber bundle architecture in atrial digital twins

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub

Molecular reconstruction and simulation of the Neuron-Glia-Vasculature system

Integrating Physics and Topology in Neural Networks for Learning Rigid Body Dynamics