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ORCIDJuan-Pablo Ortega
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2020 – today
- 2025
[j20]Jianyu Hu
, Juan-Pablo Ortega, Daiying Yin:
A Global Structure-Preserving Kernel Method for the Learning of Poisson Systems. J. Nonlinear Sci. 35(4): 79 (2025)- [c6]Giovanni Ballarin, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Memory Capacity of Nonlinear Recurrent Networks: Is It Informative? GSI (3) 2025: 53-64 - [c5]Domenico Campolo, Jianyu Hu, Juan-Pablo Ortega, Daiying Yin:
A Kernel-Based Global Method for the Learning of Elastic Potentials on Lie Groups. GSI (3) 2025: 93-102 - [i31]Giovanni Ballarin, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Memory Capacity of Nonlinear Recurrent Networks: Is it Informative? CoRR abs/2502.04832 (2025) - [i30]Jianyu Hu, Juan-Pablo Ortega, Daiying Yin:
A global structure-preserving kernel method for the learning of Poisson systems. CoRR abs/2504.13396 (2025) - [i29]Lukas Gonon, Rodrigo Martínez-Peña, Juan-Pablo Ortega:
Feedback-driven recurrent quantum neural network universality. CoRR abs/2506.16332 (2025) - [i28]Juan-Pablo Ortega, Florian Rossmannek:
Stochastic dynamics learning with state-space systems. CoRR abs/2508.07876 (2025) - [i27]Juan-Pablo Ortega, Florian Rossmannek:
Echoes of the past: A unified perspective on fading memory and echo states. CoRR abs/2508.19145 (2025) - [i26]Jianyu Hu, Juan-Pablo Ortega, Daiying Yin:
A kernel method for the learning of Wasserstein geometric flows. CoRR abs/2511.06655 (2025) - 2024
- [j19]Juan-Pablo Ortega, Daiying Yin:
Learnability of Linear Port-Hamiltonian Systems. J. Mach. Learn. Res. 25: 68:1-68:56 (2024) - [j18]Giovanni Ballarin, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Memory of recurrent networks: Do we compute it right? J. Mach. Learn. Res. 25: 243:1-243:38 (2024) - [j17]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Infinite-dimensional reservoir computing. Neural Networks 179: 106486 (2024) - [j16]Marcel Hirt, Domenico Campolo, Victoria Leong, Juan-Pablo Ortega:
Learning multi-modal generative models with permutation-invariant encoders and tighter variational objectives. Trans. Mach. Learn. Res. 2024 (2024) - [i25]Jianyu Hu, Juan-Pablo Ortega, Daiying Yin:
A Structure-Preserving Kernel Method for Learning Hamiltonian Systems. CoRR abs/2403.10070 (2024) - [i24]Juan-Pablo Ortega, Florian Rossmannek:
State-Space Systems as Dynamic Generative Models. CoRR abs/2404.08717 (2024) - [i23]Juan-Pablo Ortega, Florian Rossmannek:
Fading memory and the convolution theorem. CoRR abs/2408.07386 (2024) - [i22]Lyudmila Grigoryeva, Hannah Lim Jing Ting, Juan-Pablo Ortega:
Infinite-dimensional next-generation reservoir computing. CoRR abs/2412.09800 (2024) - 2023
- [j15]Vishal Ramanathan, Mohammad Zaidi Ariffin, Guo Dong Goh, Guo Liang Goh, Mohammad Adhimas Rikat, Xing Xi Tan, Wai Yee Yeong, Juan-Pablo Ortega, Victoria Leong, Domenico Campolo:
The Design and Development of Instrumented Toys for the Assessment of Infant Cognitive Flexibility. Sensors 23(5): 2709 (2023) - [c4]Nathaël Da Costa, Cyrus Mostajeran, Juan-Pablo Ortega:
The Gaussian Kernel on the Circle and Spaces that Admit Isometric Embeddings of the Circle. GSI (1) 2023: 426-435 - [i21]Nathaël Da Costa, Cyrus Mostajeran, Juan-Pablo Ortega:
The Gaussian kernel on the circle and spaces that admit isometric embeddings of the circle. CoRR abs/2302.10623 (2023) - [i20]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Infinite-dimensional reservoir computing. CoRR abs/2304.00490 (2023) - [i19]Giovanni Ballarin, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Memory of recurrent networks: Do we compute it right? CoRR abs/2305.01457 (2023) - [i18]Marcel Hirt, Domenico Campolo, Victoria Leong, Juan-Pablo Ortega:
Learning multi-modal generative models with permutation-invariant encoders and tighter variational bounds. CoRR abs/2309.00380 (2023) - [i17]Nathaël Da Costa, Cyrus Mostajeran, Juan-Pablo Ortega, Salem Said:
Geometric Learning with Positively Decomposable Kernels. CoRR abs/2310.13821 (2023) - [i16]Nathaël Da Costa, Cyrus Mostajeran, Juan-Pablo Ortega, Salem Said:
Invariant kernels on Riemannian symmetric spaces: a harmonic-analytic approach. CoRR abs/2310.19270 (2023) - 2022
- [j14]Gouhei Tanaka, Claudio Gallicchio, Alessio Micheli, Juan-Pablo Ortega, Akira Hirose:
Guest Editorial Special Issue on New Frontiers in Extremely Efficient Reservoir Computing. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2571-2574 (2022) - [j13]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): 6321-6330 (2022) - [i15]G. Manjunath, Juan-Pablo Ortega:
Transport in reservoir computing. CoRR abs/2209.07946 (2022) - [i14]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Reservoir kernels and Volterra series. CoRR abs/2212.14641 (2022) - 2021
- [j12]Lukas Gonon, Juan-Pablo Ortega:
Fading memory echo state networks are universal. Neural Networks 138: 10-13 (2021) - [c3]Juan-Pablo Ortega, Daiying Yin:
Expressiveness and Structure Preservation in Learning Port-Hamiltonian Systems. GSI (2) 2021: 313-322 - [i13]Lyudmila Grigoryeva, Allen Hart, Juan-Pablo Ortega:
Learning strange attractors with reservoir systems. CoRR abs/2108.05024 (2021) - 2020
- [j11]Lukas Gonon, Juan-Pablo Ortega:
Reservoir Computing Universality With Stochastic Inputs. IEEE Trans. Neural Networks Learn. Syst. 31(1): 100-112 (2020) - [i12]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Approximation Bounds for Random Neural Networks and Reservoir Systems. CoRR abs/2002.05933 (2020) - [i11]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Memory and forecasting capacities of nonlinear recurrent networks. CoRR abs/2004.11234 (2020) - [i10]Lyudmila Grigoryeva, Juan-Pablo Ortega:
Dimension reduction in recurrent networks by canonicalization. CoRR abs/2007.12141 (2020) - [i9]Lukas Gonon, Juan-Pablo Ortega:
Fading memory echo state networks are universal. CoRR abs/2010.12047 (2020) - [i8]Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann:
Discrete-time signatures and randomness in reservoir computing. CoRR abs/2010.14615 (2020)
2010 – 2019
- 2019
- [j10]Alexandru Badescu, Zhenyu Cui, Juan-Pablo Ortega:
Closed-form variance swap prices under general affine GARCH models and their continuous-time limits. Ann. Oper. Res. 282(1-2): 27-57 (2019) - [j9]Lyudmila Grigoryeva, Juan-Pablo Ortega:
Differentiable reservoir computing. J. Mach. Learn. Res. 20: 179:1-179:62 (2019) - [i7]Lyudmila Grigoryeva, Juan-Pablo Ortega:
Differentiable reservoir computing. CoRR abs/1902.06094 (2019) - [i6]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Risk bounds for reservoir computing. CoRR abs/1910.13886 (2019) - 2018
- [j8]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: 24:1-24:40 (2018) - [j7]Lyudmila Grigoryeva, Juan-Pablo Ortega:
Echo state networks are universal. Neural Networks 108: 495-508 (2018) - [i5]Lyudmila Grigoryeva, Juan-Pablo Ortega:
Echo state networks are universal. CoRR abs/1806.00797 (2018) - [i4]Lukas Gonon, Juan-Pablo Ortega:
Reservoir Computing Universality With Stochastic Inputs. CoRR abs/1807.02621 (2018) - 2017
- [i3]Lyudmila Grigoryeva, Juan-Pablo Ortega:
Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems. CoRR abs/1712.00754 (2017) - 2016
- [j6]Luc Bauwens, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Estimation and empirical performance of non-scalar dynamic conditional correlation models. Comput. Stat. Data Anal. 100: 17-36 (2016) - [j5]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): 1411-1451 (2016) - [c2]Lyudmila Grigoryeva, Julie Henriques, Laurent Larger, Juan-Pablo Ortega:
Time-Delay Reservoir Computers and High-Speed Information Processing Capacity. CSE/EUC/DCABES 2016: 492-495 - [c1]Lyudmila Grigoryeva, Julie Henriques, Juan-Pablo Ortega:
Reservoir Computing: Information Processing of Stationary Signals. CSE/EUC/DCABES 2016: 496-503 - 2015
- [j4]Alexandru Badescu, Robert J. Elliott, Juan-Pablo Ortega:
Non-Gaussian GARCH option pricing models and their diffusion limits. Eur. J. Oper. Res. 247(3): 820-830 (2015) - [i2]Lyudmila Grigoryeva, Julie Henriques, Juan-Pablo Ortega:
Forecasting, filtering, and reconstruction of stochastic stationary signals using discrete-time reservoir computers. CoRR abs/1508.00144 (2015) - [i1]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 abs/1510.03891 (2015) - 2014
- [j3]Stéphane Chrétien, Juan-Pablo Ortega:
Multivariate GARCH estimation via a Bregman-proximal trust-region method. Comput. Stat. Data Anal. 76: 210-236 (2014) - [j2]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: 59-71 (2014)
2000 – 2009
- 2003
- [j1]Pascal Chossat, Debra Lewis, Juan-Pablo Ortega, Tudor S. Ratiu:
Bifurcation of relative equilibria in mechanical systems with symmetry. Adv. Appl. Math. 31(1): 10-45 (2003)
Coauthor Index
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