82 citations · 200 across the 10 of their papers we have counts for
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Learning Schwarzschild Geodesic Motion with Lagrangian Neural Networks
Sukru Caglar, Sena Kalabalik, Abdullah Umut Hamzaogullari +1
Lagrangian Neural Networks (LNNs) learn dynamics from trajectory data by parameterizing a scalar Lagrangian and deriving accelerations through the Euler--Lagrange equation, providi…
Blind Recovery of Latent Domains via Unsupervised Symmetry Discovery
Onur Efe, Arkadas Ozakin
Primary motivation in blind inverse problems is to recover signals of interest from corrupted observations without knowing the obfuscating mechanism. Blind deconvolution is a promi…
Learning Relativistic Geodesics and Chaotic Dynamics via Stabilized Lagrangian Neural Networks
Abdullah Umut Hamzaogullari, Arkadas Ozakin
Lagrangian Neural Networks (LNNs) can learn arbitrary Lagrangians from trajectory data, but their unusual optimization objective leads to significant training instabilities that li…