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04/24/2023
Constraining Chaos: Enforcing dynamical invariants in the training of recurrent neural networks
Drawing on ergodic theory, we introduce a novel training method for mach...
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01/21/2022
A Systematic Exploration of Reservoir Computing for Forecasting Complex Spatiotemporal Dynamics
A reservoir computer (RC) is a type of simplified recurrent neural netwo...
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09/25/2021
Integrating Recurrent Neural Networks with Data Assimilation for Scalable Data-Driven State Estimation
Data assimilation (DA) is integrated with machine learning in order to p...
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02/04/2021
Forecasting Using Reservoir Computing: The Role of Generalized Synchronization
Reservoir computers (RC) are a form of recurrent neural network (RNN) us...
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11/19/2019
Machine Learning Classification Informed by a Functional Biophysical System
We present a novel machine learning architecture for classification sugg...
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07/06/2019
Precision annealing Monte Carlo methods for statistical data assimilation and machine learning
In statistical data assimilation (SDA) and supervised machine learning (...
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02/12/2019
Machine Learning of Time Series Using Time-delay Embedding and Precision Annealing
Tasking machine learning to predict segments of a time series requires e...
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01/14/2019
Precision Annealing Monte Carlo Methods for Statistical Data Assimilation: Metropolis-Hastings Procedures
Statistical Data Assimilation (SDA) is the transfer of information from ...
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05/24/2018