:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ballarin, Giovanni, Grigoryeva, Lyudmila, Ortega, Juan-Pablo
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2502.04832
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Memory of recurrent networks: Do we compute it right?
by: Ballarin, Giovanni, et al.
Published: (2023)

From Many Models, One: Macroeconomic Forecasting with Reservoir Ensembles
by: Ballarin, Giovanni, et al.
Published: (2025)

Reservoir kernels and Volterra series
by: Gonon, Lukas, et al.
Published: (2022)

Infinite-dimensional next-generation reservoir computing
by: Grigoryeva, Lyudmila, et al.
Published: (2024)

Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data
by: Ballarin, Giovanni, et al.
Published: (2022)

RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks
by: Gattiglio, Guglielmo, et al.
Published: (2024)

Forecasting causal dynamics with universal reservoirs
by: Grigoryeva, Lyudmila, et al.
Published: (2024)

Prob-GParareal: A Probabilistic Numerical Parallel-in-Time Solver for Differential Equations
by: Gattiglio, Guglielmo, et al.
Published: (2025)

Impulse Response Analysis of Structural Nonlinear Time Series Models
by: Ballarin, Giovanni
Published: (2023)

Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
by: Wang, Shida, et al.
Published: (2023)

On the Representational Capacity of Recurrent Neural Language Models
by: Nowak, Franz, et al.
Published: (2023)

Compact Recurrent Transformer with Persistent Memory
by: Mucllari, Edison, et al.
Published: (2025)

Towards Compressive and Scalable Recurrent Memory
by: Song, Yunchong, et al.
Published: (2026)

Deep Recurrent Stochastic Configuration Networks for Modelling Nonlinear Dynamic Systems
by: Dang, Gang, et al.
Published: (2024)

Recurrent Action Transformer with Memory
by: Cherepanov, Egor, et al.
Published: (2023)

Recurrent Memory for Online Interdomain Gaussian Processes
by: Chen, Wenlong, et al.
Published: (2025)

Effects of Feature Correlations on Associative Memory Capacity
by: Bielmeier, Stefan, et al.
Published: (2025)

Techniques for Enhancing Memory Capacity of Reservoir Computing
by: Yokota, Atsuki, et al.
Published: (2025)

Fading memory and the convolution theorem
by: Ortega, Juan-Pablo, et al.
Published: (2024)

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling
by: Dang, Gang, et al.
Published: (2024)

Sharp Capacity Scaling of Spectral Optimizers in Learning Associative Memory
by: Kim, Juno, et al.
Published: (2026)

Blending adversarial training and representation-conditional purification via aggregation improves adversarial robustness
by: Ballarin, Emanuele, et al.
Published: (2023)

A Dynamic Recurrent Adjacency Memory Network for Mixed-Generation Power System Stability Forecasting
by: Ooi, Guang An, et al.
Published: (2025)

A Structure-Preserving Kernel Method for Learning Hamiltonian Systems
by: Hu, Jianyu, et al.
Published: (2024)

Associative Recurrent Memory Transformer
by: Rodkin, Ivan, et al.
Published: (2024)

Learning multi-modal generative models with permutation-invariant encoders and tighter variational objectives
by: Hirt, Marcel, et al.
Published: (2023)

Deep Unrolling Networks with Recurrent Momentum Acceleration for Nonlinear Inverse Problems
by: Zhou, Qingping, et al.
Published: (2023)

Dispersion based Recurrent Neural Network Model for Methane Monitoring in Albertan Tailings Ponds
by: Saha, Esha, et al.
Published: (2024)

Spectral Pruning for Recurrent Neural Networks
by: Furuya, Takashi, et al.
Published: (2021)

Investigating Sparsity in Recurrent Neural Networks
by: Darji, Harshil
Published: (2024)

Decision Trees That Remember: Gradient-Based Learning of Recurrent Decision Trees with Memory
by: Marton, Sascha, et al.
Published: (2025)

Feedback-driven recurrent quantum neural network universality
by: Gonon, Lukas, et al.
Published: (2025)

Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers
by: Gattiglio, Guglielmo, et al.
Published: (2024)

Rethinking the Relationship between Recurrent and Non-Recurrent Neural Networks: A Study in Sparsity
by: Hershey, Quincy, et al.
Published: (2024)

Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models
by: Wu, Dennis, et al.
Published: (2024)

Understanding and inverse design of implicit bias in stochastic learning: a geometric perspective
by: Aladrah, Nicola, et al.
Published: (2026)

Recurrent Deep Differentiable Logic Gate Networks
by: Bührer, Simon, et al.
Published: (2025)

An Uncertainty Principle for Linear Recurrent Neural Networks
by: François, Alexandre, et al.
Published: (2025)

Weight-Space Linear Recurrent Neural Networks
by: Nzoyem, Roussel Desmond, et al.
Published: (2025)

Generalization and Risk Bounds for Recurrent Neural Networks
by: Cheng, Xuewei, et al.
Published: (2024)