Gauge-covariant stochastic neural fields: stability and finite-width effects. [PDF]
Terin RC.
europepmc +1 more source
HfO2‐based ferroelectrics exhibit wake‐up and fatigue behaviors during electrical cycling, significantly affecting device endurance and reliability. These phenomena are governed by defect dynamics, including oxygen vacancy redistribution and charge trapping.
Hongseok Kim +6 more
wiley +1 more source
Online physician recommendation with dynamic capacity and semantic similarity: A primal-dual optimization framework. [PDF]
Qiu Y +5 more
europepmc +1 more source
Stochastic Entanglement of Deterministic Origami Tentacles For Robust Robotic Grasping
This study introduces an origami tentacle gripper to robustly grasp objects‐in air, underwater, and even in orbital space‐by exploiting a synergy between local, deterministic deformation programming and global, stochastic entanglements. A single origami tentacle can be designed to coil with a simple tendon pull.
Alec Boron +4 more
wiley +1 more source
Conservative Numerical Framework for Fractional Stochastic Delay Modeling of CSF-1/EGF Tumor-Macrophage Aggregation. [PDF]
Mohammad M, Rihan F, Trounev A.
europepmc +1 more source
A magneto‐ionic security‐by‐materials‐design strategy exploits voltage‐driven N3– migration in selectively contacted FeCoN dots, creating reconfigurable sub‐15 nm ferromagnetic sublayers with deterministic and/or probabilistic (single‐domain↔vortex) states, voltage‐tunable probabilities and fully stochastic orientation/chirality.
Irena Spasojevic +4 more
wiley +1 more source
Everything Is Prediction: Modern Machine Learning as Bayesian Inference. [PDF]
Polson NG, Sokolov V, Soyer R.
europepmc +1 more source
Measuring human behavior through controlled perturbations: a framework for reconstructing behavioral systems. [PDF]
Cipresso P.
europepmc +1 more source
Information-geometric optimization of transient dynamics in gene regulatory networks. [PDF]
Bravetti A +3 more
europepmc +1 more source
Information Bottleneck for Communication-Efficient Multi-Agent Reinforcement Learning in UAV Swarms. [PDF]
Yang Z, Li G, Xue Y.
europepmc +1 more source

