Lyudmila Grigoryeva

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 22

Top Topics

Recurrent Networks

Reservoir Computing

Information Processing

Dimension Reduction

Top Venues

Neural Networks

J. Mach. Learn. Res.

Publications

Guglielmo Gattiglio, Lyudmila Grigoryeva, Massimiliano Tamborrino
Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers. CoRR (2024)
Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
Infinite-dimensional reservoir computing. Neural Networks 179 (2024)
Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
Infinite-dimensional reservoir computing. CoRR (2023)
Giovanni Ballarin, Lyudmila Grigoryeva, Juan-Pablo Ortega
Memory of recurrent networks: Do we compute it right? CoRR (2023)
Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann
Discrete-Time Signatures and Randomness in Reservoir Computing. IEEE Trans. Neural Networks Learn. Syst. 33 (11) (2022)
Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
Reservoir kernels and Volterra series. CoRR (2022)
Lyudmila Grigoryeva, Allen Hart, Juan-Pablo Ortega
Learning strange attractors with reservoir systems. CoRR (2021)
Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann
Discrete-time signatures and randomness in reservoir computing. CoRR (2020)
Lyudmila Grigoryeva, Juan-Pablo Ortega
Dimension reduction in recurrent networks by canonicalization. CoRR (2020)
Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
Approximation Bounds for Random Neural Networks and Reservoir Systems. CoRR (2020)
Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
Memory and forecasting capacities of nonlinear recurrent networks. CoRR (2020)
Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
Risk bounds for reservoir computing. CoRR (2019)
Lyudmila Grigoryeva, Juan-Pablo Ortega
Differentiable reservoir computing. J. Mach. Learn. Res. 20 (2019)
Lyudmila Grigoryeva, Juan-Pablo Ortega
Differentiable reservoir computing. CoRR (2019)
Lyudmila Grigoryeva, Juan-Pablo Ortega
Echo state networks are universal. Neural Networks 108 (2018)
Lyudmila Grigoryeva, Juan-Pablo Ortega
Echo state networks are universal. CoRR (2018)
Lyudmila Grigoryeva, Juan-Pablo Ortega
Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems. J. Mach. Learn. Res. 19 (2018)
Lyudmila Grigoryeva, Juan-Pablo Ortega
Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems. CoRR (2017)
Lyudmila Grigoryeva, Julie Henriques, Laurent Larger, Juan-Pablo Ortega
Nonlinear Memory Capacity of Parallel Time-Delay Reservoir Computers in the Processing of Multidimensional Signals. Neural Comput. 28 (7) (2016)
Luc Bauwens, Lyudmila Grigoryeva, Juan-Pablo Ortega
Estimation and empirical performance of non-scalar dynamic conditional correlation models. Comput. Stat. Data Anal. 100 (2016)
Lyudmila Grigoryeva, Julie Henriques, Laurent Larger, Juan-Pablo Ortega
Time-Delay Reservoir Computers and High-Speed Information Processing Capacity. CSE/EUC/DCABES (2016)
Lyudmila Grigoryeva, Julie Henriques, Juan-Pablo Ortega
Reservoir Computing: Information Processing of Stationary Signals. CSE/EUC/DCABES (2016)
Lyudmila Grigoryeva, Julie Henriques, Juan-Pablo Ortega
Forecasting, filtering, and reconstruction of stochastic stationary signals using discrete-time reservoir computers. CoRR (2015)
Lyudmila Grigoryeva, Julie Henriques, Laurent Larger, Juan-Pablo Ortega
Nonlinear memory capacity of parallel time-delay reservoir computers in the processing of multidimensional signals. CoRR (2015)
Lyudmila Grigoryeva, Julie Henriques, Laurent Larger, Juan-Pablo Ortega
Stochastic nonlinear time series forecasting using time-delay reservoir computers: Performance and universality. Neural Networks 55 (2014)