Erik M. Bollt

Clarkson University — United States

Physics and Astronomy · Physical Sciences

40h-index6.3kcitations282works1.02yr avg
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Research Topics

Chaos control and synchronization(49), Nonlinear Dynamics and Pattern Formation(45), Quantum chaos and dynamical systems(34), Model Reduction and Neural Networks(33), Neural Networks and Applications(32)

Publications281 total

KANDy: Kolmogorov-Arnold Networks and Dynamical System Discovery
ArXiv.org·2026Open Access
KANDy: Kolmogorov-Arnold Networks and Dynamical System Discovery
arXiv (Cornell University)·2026Open Access
Assimilative causal inference
Nature Communications·2026Open Access
Assimilative causal inference
Nature Communications·2026Open Access
On the emergence of numerical instabilities in next generation reservoir computing
Chaos An Interdisciplinary Journal of Nonlinear Science·2025· 1 cited
Tree-based learning for high-fidelity prediction of chaos
Scientific Reports·2025Open Access
Analysis of Tidal Flows through the Strait of Gibraltar Using Dynamic Mode Decomposition
Journal of Physical Oceanography·2025
Locality blended next-generation reservoir computing for attention accuracy
Chaos An Interdisciplinary Journal of Nonlinear Science·2025· 1 cited
On the emergence of numerical instabilities in Next Generation Reservoir Computing
arXiv (Cornell University)·2025Open Access
Data-driven model discovery with Kolmogorov-Arnold networks
Physical Review Research·2025· 13 citedOpen Access
Locality Blended Next Generation Reservoir Computing For Attention Accuracy
arXiv (Cornell University)·2025Open Access
The problem of infinite information flow
arXiv (Cornell University)·2025Open Access
Empirical Discovery of Multi-Scale Transfer of Information in Dynamical Systems
arXiv (Cornell University)·2025Open Access
How neural networks work: Unraveling the mystery of randomized neural networks for functions and chaotic dynamical systems
Chaos An Interdisciplinary Journal of Nonlinear Science·2024
Fractal Conditional Correlation Dimension Infers Complex Causal Networks
arXiv (Cornell University)·2024Open Access
On learning what to learn: Heterogeneous observations of dynamics and establishing possibly causal relations among them
PNAS Nexus·2024Open Access
Fractal Conditional Correlation Dimension Infers Complex Causal Networks
Entropy·2024· 1 citedOpen Access
Symmetry breaker governs synchrony patterns in neuronal inspired networks
Chaos An Interdisciplinary Journal of Nonlinear Science·2024
Kolmogorov-Arnold Network Autoencoders
arXiv (Cornell University)·2024· 3 citedOpen Access
Data-driven model discovery with Kolmogorov-Arnold networks
arXiv (Cornell University)·2024Open Access
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Frequent Co-authors

Jie Sun(8), Joseph D. Skufca(6), Maurizio Porfiri(5), Daniel J. Stilwell(4), Lora Billings(4), Ying-Cheng Lai(3), Ying‐Cheng Lai(3), Stephen J. McGregor(3), Ira B. Schwartz(3), James P. Bagrow(2), Daniel ben‐Avraham(2), Celso Grebogi(2), Theodore Stanford(2), Karol Życzkowski(2), Rick Chartrand(2), Kevin R. Vixie(2), James D. Meiss(2), Michael A. Busa(2), James A. Yaggie(2), Naratip Santitissadeekorn(2)