4 citations · 7 across the 5 of their papers we have counts for
5 papers
Optimized Architectures for Kolmogorov-Arnold Networks
James Bagrow, Josh Bongard
Efforts to improve Kolmogorov--Arnold networks (KANs) with architectural enhancements have been stymied by the complexity those enhancements bring, undermining the interpretability…
Softly Symbolifying Kolmogorov-Arnold Networks
James Bagrow, Josh Bongard
Kolmogorov--Arnold Networks (KANs) offer a promising path toward interpretable machine learning: their learnable activations can be studied individually while collectively fitting…
Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony
James Bagrow, Josh Bongard
Kolmogorov-Arnold Networks (KANs) uniquely combine high accuracy with interpretability, making them valuable for scientific modeling. However, it is unclear a priori how deep a net…
[RETRACTED]Evolving Form and Function: Dual-Objective Optimization in Neural Symbolic Regression Networks
Amanda Bertschinger, James Bagrow, Joshua Bongard
[RETRACTED]Data increasingly abounds, but distilling their underlying relationships down to something interpretable remains challenging. One approach is genetic programming, which…
Data-driven Modeling of Granular Chains with Modern Koopman Theory
Atoosa Parsa, James Bagrow, Corey S. O'Hern +2
Externally driven dense packings of particles can exhibit nonlinear wave phenomena that are not described by effective medium theory or linearized approximate models. Such nontrivi…