440 citations · 455 across the 8 of their papers we have counts for
8 papers
Uncovering Extreme Event Mechanisms for Prediction and Control with Sensitivity-Balanced Projections
Nicholas Zolman, Sajeda Mokbel, Samuel E. Otto +1
Extreme events -- such as earthquakes and coronal mass ejections -- are common in many chaotic dynamical systems, yet are difficult to characterize and predict due to the subtle in…
SINDy-KANs: Sparse identification of non-linear dynamics through Kolmogorov-Arnold networks
Amanda A. Howard, Nicholas Zolman, Bruno Jacob +2
Kolmogorov-Arnold networks (KANs) have arisen as a potential way to enhance the interpretability of machine learning. However, solutions learned by KANs are not necessarily interpr…
The HydroGym Reinforcement Learning Platform for Fluid Dynamics
Christian Lagemann, Sajeda Mokbel, Miro Gondrum +18
Modeling and controlling fluids is critical across science and engineering. Effective flow control can increase lift, reduce drag, enhance mixing, and attenuate noise, potentially…
SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning
Nicholas Zolman, Christian Lagemann, Urban Fasel +2
Deep reinforcement learning (DRL) has shown significant promise for uncovering sophisticated control policies that interact in complex environments, such as stabilizing a tokamak f…
A Unified Framework to Enforce, Discover, and Promote Symmetry in Machine Learning
Samuel E. Otto, Nicholas Zolman, J. Nathan Kutz +1
Symmetry is present throughout nature and continues to play an increasingly central role in physics and machine learning. Fundamental symmetries, such as Poincaré invariance, allow…
Learning to Predict 3D Rotational Dynamics from Images of a Rigid Body with Unknown Mass Distribution
Justice Mason, Christine Allen-Blanchette, Nicholas Zolman +2
In many real-world settings, image observations of freely rotating 3D rigid bodies may be available when low-dimensional measurements are not. However, the high-dimensionality of i…
Learning Interpretable Dynamics from Images of a Freely Rotating 3D Rigid Body
Justice Mason, Christine Allen-Blanchette, Nicholas Zolman +2
In many real-world settings, image observations of freely rotating 3D rigid bodies, such as satellites, may be available when low-dimensional measurements are not. However, the hig…
The Origin and Evolution of the Galaxy Mass-Metallicity Relation
Xiangcheng Ma, Philip F. Hopkins, Claude-Andre Faucher-Giguere +4
We use high-resolution cosmological zoom-in simulations from the Feedback in Realistic Environment (FIRE) project to study the galaxy mass-metallicity relations (MZR) from z=0-6. T…