A theoretical framework for reservoir computing on networks of organic electrochemical transistors
Fuente:
arXiv
Guardado en:
| Autores principales: | Landry, Nicholas W., Hyde, Beckett R., Perez, Jake C., Shaheen, Sean E., Restrepo, Juan G. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Reservoir computing with large valid prediction time for the Lorenz system
por: Hurley, Lauren A, et al.
Publicado: (2025)
por: Hurley, Lauren A, et al.
Publicado: (2025)
TDE-3: An improved prior for optical flow computation in spiking neural networks
por: Yedutenko, Matthew, et al.
Publicado: (2024)
por: Yedutenko, Matthew, et al.
Publicado: (2024)
Neuromorphic on-chip reservoir computing with spiking neural network architectures
por: Karki, Samip, et al.
Publicado: (2024)
por: Karki, Samip, et al.
Publicado: (2024)
Infinite-dimensional next-generation reservoir computing
por: Grigoryeva, Lyudmila, et al.
Publicado: (2024)
por: Grigoryeva, Lyudmila, et al.
Publicado: (2024)
Practical design and performance of physical reservoir computing using hysteresis
por: Yamada, Yuhei
Publicado: (2025)
por: Yamada, Yuhei
Publicado: (2025)
Universality of reservoir systems with recurrent neural networks
por: Yasumoto, Hiroki, et al.
Publicado: (2024)
por: Yasumoto, Hiroki, et al.
Publicado: (2024)
Asymmetrically connected reservoir networks learn better
por: Rathor, Shailendra K., et al.
Publicado: (2024)
por: Rathor, Shailendra K., et al.
Publicado: (2024)
Exploiting heterogeneous delays for efficient computation in low-bit neural networks
por: Sun, Pengfei, et al.
Publicado: (2025)
por: Sun, Pengfei, et al.
Publicado: (2025)
Elucidating the theoretical underpinnings of surrogate gradient learning in spiking neural networks
por: Gygax, Julia, et al.
Publicado: (2024)
por: Gygax, Julia, et al.
Publicado: (2024)
Oscillations enhance time-series prediction in reservoir computing with feedback
por: Kawai, Yuji, et al.
Publicado: (2024)
por: Kawai, Yuji, et al.
Publicado: (2024)
Exploring the origins of switching dynamics in a multifunctional reservoir computer
por: Flynn, Andrew, et al.
Publicado: (2024)
por: Flynn, Andrew, et al.
Publicado: (2024)
A flexible framework for structural plasticity in GPU-accelerated sparse spiking neural networks
por: Knight, James C., et al.
Publicado: (2025)
por: Knight, James C., et al.
Publicado: (2025)
GeNeX: Genetic Network eXperts framework for addressing Validation Overfitting
por: Pintelas, Emmanuel, et al.
Publicado: (2026)
por: Pintelas, Emmanuel, et al.
Publicado: (2026)
Developing a novel Comorbidities Index for predicting 10-year mortality in Prostate Cancer patients: A computational data-driven approach
por: Farinati, Davide, et al.
Publicado: (2026)
por: Farinati, Davide, et al.
Publicado: (2026)
Waves and symbols in neuromorphic hardware: from analog signal processing to digital computing on the same computational substrate
por: Zendrikov, Dmitrii, et al.
Publicado: (2025)
por: Zendrikov, Dmitrii, et al.
Publicado: (2025)
Spike-based computation using classical recurrent neural networks
por: De Geeter, Florent, et al.
Publicado: (2023)
por: De Geeter, Florent, et al.
Publicado: (2023)
Using evolutionary computation to optimize task performance of unclocked, recurrent Boolean circuits in FPGAs
por: Norman-Tenazas, Raphael, et al.
Publicado: (2024)
por: Norman-Tenazas, Raphael, et al.
Publicado: (2024)
Evolutionary feature selection for spiking neural network pattern classifiers
por: Valko, Michal, et al.
Publicado: (2026)
por: Valko, Michal, et al.
Publicado: (2026)
DelRec: learning delays in recurrent spiking neural networks
por: Queant, Alexandre, et al.
Publicado: (2025)
por: Queant, Alexandre, et al.
Publicado: (2025)
A computational approach to visual ecology with deep reinforcement learning
por: Sokoloski, Sacha, et al.
Publicado: (2024)
por: Sokoloski, Sacha, et al.
Publicado: (2024)
Bellman Memory Units: A neuromorphic framework for synaptic reinforcement learning with an evolving network topology
por: Banerjee, Shreyan, et al.
Publicado: (2025)
por: Banerjee, Shreyan, et al.
Publicado: (2025)
Neuromorphic Keyword Spotting with Pulse Density Modulation MEMS Microphones
por: Yarga, Sidi Yaya Arnaud, et al.
Publicado: (2024)
por: Yarga, Sidi Yaya Arnaud, et al.
Publicado: (2024)
Effects of cavity nonlinearities and linear losses on silicon microring-based reservoir computing
por: Castro, Bernard J. Giron, et al.
Publicado: (2023)
por: Castro, Bernard J. Giron, et al.
Publicado: (2023)
How more data can hurt: Instability and regularization in next-generation reservoir computing
por: Zhang, Yuanzhao, et al.
Publicado: (2024)
por: Zhang, Yuanzhao, et al.
Publicado: (2024)
Information flow and Laplacian dynamics on local optima networks
por: Richter, Hendrik, et al.
Publicado: (2024)
por: Richter, Hendrik, et al.
Publicado: (2024)
The working principles of model-based GAs fall within the PAC framework: A mathematical theory of problem decomposition
por: Yu, Tian-Li, et al.
Publicado: (2025)
por: Yu, Tian-Li, et al.
Publicado: (2025)
Automated Optimal Layout Generator for Animal Shelters: A framework based on Genetic Algorithm, TOPSIS and Graph Theory
por: Jalayer, Arghavan, et al.
Publicado: (2024)
por: Jalayer, Arghavan, et al.
Publicado: (2024)
Physics-informed neural network for modeling dynamic linear elasticity
por: Kag, Vijay, et al.
Publicado: (2023)
por: Kag, Vijay, et al.
Publicado: (2023)
Efficient event-driven retrieval in high-capacity kernel Hopfield networks
por: Tamamori, Akira
Publicado: (2026)
por: Tamamori, Akira
Publicado: (2026)
Algorithm-hardware co-design of neuromorphic networks with dual memory pathways
por: Sun, Pengfei, et al.
Publicado: (2025)
por: Sun, Pengfei, et al.
Publicado: (2025)
Reservoir computing with logistic map
por: Arun, R., et al.
Publicado: (2024)
por: Arun, R., et al.
Publicado: (2024)
A two-stage algorithm in evolutionary product unit neural networks for classification
por: Tallón-Ballesteros, Antonio J., et al.
Publicado: (2024)
por: Tallón-Ballesteros, Antonio J., et al.
Publicado: (2024)
Towards free-response paradigm: a theory on decision-making in spiking neural networks
por: Zhu, Zhichao, et al.
Publicado: (2024)
por: Zhu, Zhichao, et al.
Publicado: (2024)
Cognition without neurons: modelling anticipation in a basal reservoir computer
por: Bruna, Polyphony, et al.
Publicado: (2025)
por: Bruna, Polyphony, et al.
Publicado: (2025)
When Spiking neural networks meet temporal attention image decoding and adaptive spiking neuron
por: Qiu, Xuerui, et al.
Publicado: (2024)
por: Qiu, Xuerui, et al.
Publicado: (2024)
Von Economo neurons enable reliable social skill acquisition in recurrent spiking neural networks: a computational account with clinical predictions
por: Keskin, Esila
Publicado: (2026)
por: Keskin, Esila
Publicado: (2026)
STCSNN: High energy efficiency spike-train level spiking neural networks with spatio-temporal conversion
por: Xu, Changqing, et al.
Publicado: (2023)
por: Xu, Changqing, et al.
Publicado: (2023)
Parameter efficient hybrid spiking-quantum convolutional neural network with surrogate gradient and quantum data-reupload
por: Nhan, Luu Trong, et al.
Publicado: (2025)
por: Nhan, Luu Trong, et al.
Publicado: (2025)
Non-Dominated Sorting Bidirectional Differential Coevolution
por: Mendes, Cicero S. R., et al.
Publicado: (2024)
por: Mendes, Cicero S. R., et al.
Publicado: (2024)
Implementation of high-efficiency, lightweight residual spiking neural network processor based on field-programmable gate arrays
por: Yue, Hou, et al.
Publicado: (2025)
por: Yue, Hou, et al.
Publicado: (2025)
Ejemplares similares
-
Reservoir computing with large valid prediction time for the Lorenz system
por: Hurley, Lauren A, et al.
Publicado: (2025) -
TDE-3: An improved prior for optical flow computation in spiking neural networks
por: Yedutenko, Matthew, et al.
Publicado: (2024) -
Neuromorphic on-chip reservoir computing with spiking neural network architectures
por: Karki, Samip, et al.
Publicado: (2024) -
Infinite-dimensional next-generation reservoir computing
por: Grigoryeva, Lyudmila, et al.
Publicado: (2024) -
Practical design and performance of physical reservoir computing using hysteresis
por: Yamada, Yuhei
Publicado: (2025)