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Frontiers | Generative Models of Brain Dynamics
Frontiers | Generative Models of Brain Dynamics

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect

Embracing Change: Continual Learning in Deep Neural Networks: Trends in  Cognitive Sciences
Embracing Change: Continual Learning in Deep Neural Networks: Trends in Cognitive Sciences

Next generation reservoir computing | Nature Communications
Next generation reservoir computing | Nature Communications

11 The system dynamics modeling process | Download Scientific Diagram
11 The system dynamics modeling process | Download Scientific Diagram

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect

Dynamics and Optimization of Learning Systems (DOLS) | Earth Signals and  Systems Group
Dynamics and Optimization of Learning Systems (DOLS) | Earth Signals and Systems Group

Modeling of dynamical systems through deep learning | SpringerLink
Modeling of dynamical systems through deep learning | SpringerLink

Artificial neural network - Wikipedia
Artificial neural network - Wikipedia

Long-Time-Step Molecular Dynamics through Hydrogen Mass Repartitioning |  Journal of Chemical Theory and Computation
Long-Time-Step Molecular Dynamics through Hydrogen Mass Repartitioning | Journal of Chemical Theory and Computation

Closed-form continuous-time neural networks | Nature Machine Intelligence
Closed-form continuous-time neural networks | Nature Machine Intelligence

Machine Learning Force Fields and Coarse-Grained Variables in Molecular  Dynamics: Application to Materials and Biological Systems | Journal of  Chemical Theory and Computation
Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems | Journal of Chemical Theory and Computation

Applied Sciences | Free Full-Text | Re-Thinking Data Strategy and  Integration for Artificial Intelligence: Concepts, Opportunities, and  Challenges
Applied Sciences | Free Full-Text | Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges

Machine learning dismantling and early-warning signals of disintegration in  complex systems | Nature Communications
Machine learning dismantling and early-warning signals of disintegration in complex systems | Nature Communications

Time series in healthcare: challenges and solutions // van der Schaar Lab
Time series in healthcare: challenges and solutions // van der Schaar Lab

From Computational Fluid Dynamics to Structure Interpretation via Neural  Networks: An Application to Flow and Transport in Porous Media | Industrial  & Engineering Chemistry Research
From Computational Fluid Dynamics to Structure Interpretation via Neural Networks: An Application to Flow and Transport in Porous Media | Industrial & Engineering Chemistry Research

Real-Time Adaptive Machine-Learning-Based Predictive Control of Nonlinear  Processes | Industrial & Engineering Chemistry Research
Real-Time Adaptive Machine-Learning-Based Predictive Control of Nonlinear Processes | Industrial & Engineering Chemistry Research

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect

From calibration to parameter learning: Harnessing the scaling effects of  big data in geoscientific modeling | Nature Communications
From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modeling | Nature Communications

Dynamic and explainable machine learning prediction of mortality in  patients in the intensive care unit: a retrospective study of  high-frequency data in electronic patient records - The Lancet Digital  Health
Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records - The Lancet Digital Health

A review of dynamical systems approaches for the detection of chaotic  attractors in cancer networks - ScienceDirect
A review of dynamical systems approaches for the detection of chaotic attractors in cancer networks - ScienceDirect

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect

Self-directed online machine learning for topology optimization | Nature  Communications
Self-directed online machine learning for topology optimization | Nature Communications

Learning dynamical systems from data: A simple cross-validation  perspective, Part III: Irregularly-sampled time series - ScienceDirect
Learning dynamical systems from data: A simple cross-validation perspective, Part III: Irregularly-sampled time series - ScienceDirect