Roughness on ice surfaces produces localized droplet impingement that drives a feedback loop amplifying existing roughness features over time.
Understanding brain states across spacetime informed by whole-brain modelling
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
years
2026 6roles
background 2polarities
background 2representative citing papers
Tensor network model achieves 77.98% accuracy in modeling order-dependent emotional memory in children.
Generalized saddle-node ghosts are defined for higher-dimensional systems with algorithms to detect ghost attractors, channels, and cycles, implemented in the PyGhostID Python package.
Proposes functional whole-brain models defined by four criteria that integrate empirical connectomes, dynamical realism, and task-performing competence across cognitive domains.
The paper introduces Recursive QLSTM via metacore recursion, numerically tests variants on sequence lengths, and offers theoretical arguments for better temporal propagation.
citing papers explorer
-
LES of Droplet Impingement: Application to Clean and Laser-Scanned Ice Shapes
Roughness on ice surfaces produces localized droplet impingement that drives a feedback loop amplifying existing roughness features over time.
-
Modelling Emotional Memory in Children with Tensor Networks
Tensor network model achieves 77.98% accuracy in modeling order-dependent emotional memory in children.
-
Generalized saddle-node ghosts and their composite structures in dynamical systems
Generalized saddle-node ghosts are defined for higher-dimensional systems with algorithms to detect ghost attractors, channels, and cycles, implemented in the PyGhostID Python package.
-
Functional Whole-Brain Models: A New Framework for Unifying Brain Structure and Cognitive Function
Proposes functional whole-brain models defined by four criteria that integrate empirical connectomes, dynamical realism, and task-performing competence across cognitive domains.
-
Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptation
The paper introduces Recursive QLSTM via metacore recursion, numerically tests variants on sequence lengths, and offers theoretical arguments for better temporal propagation.
- Descent Before Hardness: Orbit-Gap Obstructions in Exact Certification