Zobrazeno 1 - 10
of 82
pro vyhledávání: '"Platt, Jason"'
The immense computational cost of traditional numerical weather and climate models has sparked the development of machine learning (ML) based emulators. Because ML methods benefit from long records of training data, it is common to use datasets that
Externí odkaz:
http://arxiv.org/abs/2305.00100
Autor:
Platt, Jason A., Penny, Stephen G., Smith, Timothy A., Chen, Tse-Chun, Abarbanel, Henry D. I.
Drawing on ergodic theory, we introduce a novel training method for machine learning based forecasting methods for chaotic dynamical systems. The training enforces dynamical invariants--such as the Lyapunov exponent spectrum and fractal dimension--in
Externí odkaz:
http://arxiv.org/abs/2304.12865
Autor:
Platt, Jason A., Penny, Stephen G., Smith, Timothy A., Chen, Tse-Chun, Abarbanel, Henry D. I.
A reservoir computer (RC) is a type of simplified recurrent neural network architecture that has demonstrated success in the prediction of spatiotemporally chaotic dynamical systems. A further advantage of RC is that it reproduces intrinsic dynamical
Externí odkaz:
http://arxiv.org/abs/2201.08910
Next generation reservoir computing based on nonlinear vector autoregression (NVAR) is applied to emulate simple dynamical system models and compared to numerical integration schemes such as Euler and the $2^\text{nd}$ order Runge-Kutta. It is shown
Externí odkaz:
http://arxiv.org/abs/2201.05193
Autor:
Penny, Stephen G., Smith, Timothy A., Chen, Tse-Chun, Platt, Jason A., Lin, Hsin-Yi, Goodliff, Michael, Abarbanel, Henry D. I.
Data assimilation (DA) is integrated with machine learning in order to perform entirely data-driven online state estimation. To achieve this, recurrent neural networks (RNNs) are implemented as surrogate models to replace key components of the DA cyc
Externí odkaz:
http://arxiv.org/abs/2109.12269
Reservoir computers (RC) are a form of recurrent neural network (RNN) used for forecasting timeseries data. As with all RNNs, selecting the hyperparameters presents a challenge when training onnew inputs. We present a method based on generalized sync
Externí odkaz:
http://arxiv.org/abs/2103.00362
Reservoir computers (RC) are a form of recurrent neural network (RNN) used for forecasting time series data. As with all RNNs, selecting the hyperparameters presents a challenge when training on new inputs. We present a method based on generalized sy
Externí odkaz:
http://arxiv.org/abs/2102.08930
We present a novel machine learning architecture for classification suggested by experiments on olfactory systems. The network separates input stimuli, represented as spatially distinct currents, via winnerless competition---a process based on the in
Externí odkaz:
http://arxiv.org/abs/1911.08589
For the Research Topic Data Assimilation and Control: Theory and Applications in Life Sciences we first review the formulation of statistical data assimilation (SDA) and discuss algorithms for exploring variational approximations to the conditional e
Externí odkaz:
http://arxiv.org/abs/1809.05196
Autor:
Hoskins, David, Platt, Jason
Publikováno v:
The Journal of Mental Health Training, Education and Practice, 2021, Vol. 17, Issue 2, pp. 159-177.
