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Reservoir Computing Universality With Stochastic Inputs

IEEE transaction on neural networks and learning systems, 2020-01, Vol.31 (1), p.100-112

2020

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Discrete-Time Signatures and Randomness in Reservoir Computing

IEEE transaction on neural networks and learning systems, 2022-11, Vol.33 (11), p.6321-6330

2022

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Closed-form variance swap prices under general affine GARCH models and their continuous-time limits

Annals of operations research, 2019-11, Vol.282 (1-2), p.27-57

2019

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Predicting U.S. Bank Failures with MIDAS Logit Models

Journal of financial and quantitative analysis, 2019-12, Vol.54 (6), p.2575-2603

2019

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Guest Editorial Special Issue on New Frontiers in Extremely Efficient Reservoir Computing

IEEE transaction on neural networks and learning systems, 2022-06, Vol.33 (6), p.2571-2574

2022

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Echo state networks are universal

Neural networks, 2018-12, Vol.108, p.495-508

2018

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Optimal nonlinear information processing capacity in delay-based reservoir computers

Scientific reports, 2015-09, Vol.5 (1), p.12858-12858, Article 12858

2015

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Nonlinear Memory Capacity of Parallel Time-Delay Reservoir Computers in the Processing of Multidimensional Signals

Neural computation, 2016-07, Vol.28 (7), p.1411-1451

2016

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The Design and Development of Instrumented Toys for the Assessment of Infant Cognitive Flexibility

Sensors (Basel, Switzerland), 2023-03, Vol.23 (5), p.2709

2023

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Fading memory echo state networks are universal

Neural networks, 2021-06, Vol.138, p.10-13

2021

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Memory and forecasting capacities of nonlinear recurrent networks

Physica. D, 2020-12, Vol.414, p.132721, Article 132721

2020

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Approximation bounds for random neural networks and reservoir systems

The Annals of applied probability, 2023-02, Vol.33 (1), p.28

2023

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Transport in reservoir computing

Physica. D, 2023-07, Vol.449, p.133744, Article 133744

2023

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Learning strange attractors with reservoir systems

Nonlinearity, 2023-09, Vol.36 (9), p.4674-4708

2023

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Tracing curves in the plane: Geometric-invariant learning from human demonstrations

PloS one, 2024-02, Vol.19 (2), p.e0294046-e0294046

2024

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Chaos on compact manifolds: Differentiable synchronizations beyond the Takens theorem

Physical review. E, 2021-06, Vol.103 (6), Article 062204

2021

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Reservoir computing for macroeconomic forecasting with mixed-frequency data

International journal of forecasting, 2024-07, Vol.40 (3), p.1206-1237

2024

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Dimension reduction in recurrent networks by canonicalization

Journal of geometric mechanics, 2021-12, Vol.13 (4), p.647

2021

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Bedside Evaluation of the Functional Organization of the Auditory Cortex in Patients with Disorders of Consciousness

PloS one, 2016-01, Vol.11 (1), p.e0146788-e0146788

2016

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A Simple Formula for the Hilbert Metric with Respect to a Sub-Gaussian Cone

Mathematics (Basel), 2018-03, Vol.6 (3), p.35

2018

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Non-affine GARCH Option Pricing Models, Variance-Dependent Kernels, and Diffusion Limits

Journal of financial econometrics, 2017-09, Vol.15 (4), p.602-648

2017

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Quantum reservoir computing in finite dimensions

Physical review. E, 2023-03, Vol.107 (3), Article 035306

2023

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Hybrid Forecasting with Estimated Temporally Aggregated Linear Processes

Journal of forecasting, 2014-12, Vol.33 (8), p.577-595

2014

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Stochastic nonlinear time series forecasting using time-delay reservoir computers: Performance and universality

Neural networks, 2014-07, Vol.55, p.59-71

2014

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Non-Gaussian GARCH option pricing models and their diffusion limits

European journal of operational research, 2015-12, Vol.247 (3), p.820-830

2015

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Reservoir Computing Universality With Stochastic Inputs

Discrete-Time Signatures and Randomness in Reservoir Computing

Closed-form variance swap prices under general affine GARCH models and their continuous-time limits

Predicting U.S. Bank Failures with MIDAS Logit Models

Guest Editorial Special Issue on New Frontiers in Extremely Efficient Reservoir Computing

Echo state networks are universal

Optimal nonlinear information processing capacity in delay-based reservoir computers

Nonlinear Memory Capacity of Parallel Time-Delay Reservoir Computers in the Processing of Multidimensional Signals

The Design and Development of Instrumented Toys for the Assessment of Infant Cognitive Flexibility

Fading memory echo state networks are universal

Memory and forecasting capacities of nonlinear recurrent networks

Approximation bounds for random neural networks and reservoir systems

Transport in reservoir computing

Learning strange attractors with reservoir systems

Tracing curves in the plane: Geometric-invariant learning from human demonstrations

Chaos on compact manifolds: Differentiable synchronizations beyond the Takens theorem

Reservoir computing for macroeconomic forecasting with mixed-frequency data

Dimension reduction in recurrent networks by canonicalization

Bedside Evaluation of the Functional Organization of the Auditory Cortex in Patients with Disorders of Consciousness

A Simple Formula for the Hilbert Metric with Respect to a Sub-Gaussian Cone

Non-affine GARCH Option Pricing Models, Variance-Dependent Kernels, and Diffusion Limits

Quantum reservoir computing in finite dimensions

Hybrid Forecasting with Estimated Temporally Aggregated Linear Processes

Stochastic nonlinear time series forecasting using time-delay reservoir computers: Performance and universality

Non-Gaussian GARCH option pricing models and their diffusion limits

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