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Temporally-Consistent Koopman Autoencoders for Forecasting Dynamical Systems
Absence of sufficiently high-quality data often poses a key challenge in data-driven modeling of high-dimensional spatio-temporal dynamical systems.
On the Predictive Capability of Dynamic Mode Decomposition for Nonlinear Periodic Systems with Focus on Orbital Mechanics
This paper discusses the predictive capability of Dynamic Mode Decomposition (DMD) in the context of orbital mechanics.
Monotone Circuit Lower Bounds from Robust Sunflowers
Robust sunflowers are a generalization of combinatorial sunflowers that have applications in monotone circuit complexity, DNF sparsification, randomness extractors, and recent advances on the Erd\H{o}s-Rado sunflower conjecture.
Computational Complexity
