John Lindner

Cohen-Cobos, D., Sanders, K., DeGroot, L., Guarnera, H., Leary, C., Lindner, J. F., & Manz, N. (2024). Chemistry does general relativity: reaction-diffusion waves can model gravitational lensing. FRONTIERS IN PHYSICS, 11. https://doi.org/10.3389/fphy.2023.1315966

Fuller, C. A., Cohen-Cobos, D., Lindner, J. F., & Manz, N. (2024). Light-Sensitive Diffusion Diodes for Reaction-Diffusion Waves. INTERNATIONAL JOURNAL OF UNCONVENTIONAL COMPUTING, 19(1), 1–15. https://doi.org/10.32908/ijuc.v19.200823

Choudhary, A., Radhakrishnan, A., Lindner, J. F., Sinha, S., & Ditto, W. L. (2023). Neuronal diversity can improve machine learning for physics and beyond. SCIENTIFIC REPORTS, 13(1). https://doi.org/10.1038/s41598-023-40766-6

Holliday, E. G. G., Lindner, J. F. F., & Ditto, W. L. L. (2023). Solving quantum billiard eigenvalue problems with physics-informed machine learning. AIP ADVANCES, 13(8). https://doi.org/10.1063/5.0161067

Xie, X., Bae, H., & Lindner, J. F. (2022). Alien suns reversing in exoplanet skies. SCIENTIFIC REPORTS, 12(1). https://doi.org/10.1038/s41598-022-11527-8

Choudhary, A., Lindner, J. F., Holliday, E. G., Miller, S. T., Sinha, S., & Ditto, W. L. (2021). Forecasting Hamiltonian dynamics without canonical coordinates. NONLINEAR DYNAMICS, 103(2), 1553–1562. https://doi.org/10.1007/s11071-020-06185-2

Miller, S. T., Lindner, J. F., Choudhary, A., Sinha, S., & Ditto, W. L. (2021). Negotiating the separatrix with machine learning. IEICE NONLINEAR THEORY AND ITS APPLICATIONS, 12(2), 134–142. https://doi.org/10.1587/nolta.12.134