14 citations · 26 across the 14 of their papers we have counts for
15 papers
Higher-Order Kolmogorov-Arnold Networks for Dynamics
Kevin Slote, Jeremie Fish
The ability to derive the governing equations of a dynamical system from data is essential for prediction and control across many scientific fields. Two challenges, however, are th…
Memorial for Dr. Erik Bollt
Scott Bollt, Mario di Bernardo, Jeremie Fish +4
In this paper, we give a memorial tribute to Prof. Erik M. Bollt (1967--2025).
Deep-Koopman-KANDy: Dictionary Discovery for Deep-Koopman Operators with Kolmogorov-Arnold Networks for Dynamics
Kevin Slote, Erik Bollt, Jeremie Fish
Symbolic library -- or Koopman dictionary -- selection is a fundamental challenge in data-driven dynamical systems. Extended Dynamic Mode Decomposition (EDMD), Sparse Identificatio…
KANDy: Kolmogorov-Arnold Networks and Dynamical System Discovery
Kevin Slote, Jeremie Fish, Erik Bollt
We introduce the Kolmogorov-Arnold Network for Dynamics (KANDy) as a zero-depth, wide neural architecture capable of discovering governing equations in chaotic and complex dynamica…
CausationEntropy: Pythonic Optimal Causation Entropy
Kevin Slote, Jeremie Fish, Erik Bollt
Optimal Causation Entropy (oCSE) is a robust causal network modeling technique that reveals causal networks from dynamical systems and coupled oscillators, distinguishing direct fr…
Fractal Basins as a Mechanism for the Nimble Brain
Erik Bollt, Jeremie Fish, Anil Kumar +2
An interesting feature of the brain is its ability to respond to disparate sensory signals from the environment in unique ways depending on the environmental context or current bra…
Learning Transfer Operators by Kernel Density Estimation
Sudam Surasinghe, Jeremie Fish, Erik M. Bollt
Inference of transfer operators from data is often formulated as a classical problem that hinges on the Ulam method. The conventional description, known as the Ulam-Galerkin method…
How fragile is your network? More than you think
Jeremie Fish, Mahesh Banavar, Erik Bollt
Graphs are pervasive in our everyday lives, with relevance to biology, the internet, and infrastructure, as well as numerous other applications. It is thus necessary to have an und…
Non-normality, optimality and synchronization
Jeremie Fish, Erik M. Bollt
It has been recognized for quite some time that for some matrices the spectra are not enough to tell the complete story of the dynamics of the system, even for linear ODEs. While i…
The Essential Synchronization Backbone Problem
C. Tyler Diggans, Jeremie Fish, Abd AlRahman R. AlMomani +1
Network optimization strategies for the process of synchronization have generally focused on the re-wiring or re-weighting of links in order to: (1) expand the range of coupling st…
Beach-level 24-hour forecasts of Florida red tide-induced respiratory irritation
Shane D. Ross, Jeremie Fish, Klaus Moeltner +3
An accurate forecast of the red tide respiratory irritation level would improve the lives of many people living in areas affected by algal blooms. Using a decades-long database of…
Emergent hierarchy through conductance-based node constraints
C. Tyler Diggans, Jeremie Fish, Erik Bollt
The presence of hierarchy in many real-world networks is not yet fully explained. Complex interaction networks are often coarse-grain models of vast modular networks, where tightly…
Entropic Causal Inference for Neurological Applications
Jeremie Fish, Alexander DeWitt, Abd AlRahman R. AlMomani +2
The ultimate goal of cognitive neuroscience is to understand the mechanistic neural processes underlying the functional organization of the brain. Key to this study is understandin…
Interaction Networks from Discrete Event Data by Poisson Multivariate Mutual Information Estimation and Information Flow with Applications from Gene Expression Data
Jeremie Fish, Jie Sun, Erik Bollt
In this work, we introduce a new methodology for inferring the interaction structure of discrete valued time series which are Poisson distributed. While most related methods are pr…
Construction,sensitivity index, and synchronization speed of optimal networks
Jeremie Fish, Jie Sun
The stability (or instability) of synchronization is important in a number of real world systems, including the power grid, the human brain and biological cells. For identical sync…