Pre-computed Liquid Spaces with Generative Neural Networks and Optical Flow. - Boris Bonev; Lukas Prantl; Nils Thuerey (CoRR, 2017)

Discontinuous Galerkin scheme for the spherical shallow water equations with applications to tsunami modeling and prediction. - Boris Bonev; Jan S. Hesthaven; Francis X. Giraldo; Michal A. Kopera (J. Comput. Phys., 2018)

Generating Liquid Simulations with Deformation-aware Neural Networks. - Lukas Prantl; Boris Bonev; Nils Thuerey (ICLR (Poster), 2019)

A Hierarchical Preconditioner for Wave Problems in Quasilinear Complexity. - Boris Bonev; Jan S. Hesthaven (SIAM J. Sci. Comput., 2022)

Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere. - Boris Bonev; Thorsten Kurth; Christian Hundt 002; Jaideep Pathak; Maximilian Baust; Karthik Kashinath; Anima Anandkumar (ICML, 2023)

ACE: A fast, skillful learned global atmospheric model for climate prediction. - Oliver Watt-Meyer; Gideon Dresdner; Jeremy McGibbon; Spencer K. Clark; Brian Henn; James Duncan 002; Noah D. Brenowitz; Karthik Kashinath; Michael S. Pritchard; Boris Bonev; Matthew E. Peters; Christopher S. Bretherton (CoRR, 2023)

Guaranteed Approximation Bounds for Mixed-Precision Neural Operators. - Renbo Tu; Colin White; Jean Kossaifi; Boris Bonev; Gennady Pekhimenko; Kamyar Azizzadenesheli; Anima Anandkumar (ICLR, 2024)

Neural Operators with Localized Integral and Differential Kernels. - Miguel Liu-Schiaffini; Julius Berner; Boris Bonev; Thorsten Kurth; Kamyar Azizzadenesheli; Anima Anandkumar (ICML, 2024)

Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs. - Md. Ashiqur Rahman; Robert Joseph George; Mogab Elleithy; Daniel V. Leibovici; Zongyi Li; Boris Bonev; Colin White; Julius Berner; Raymond A. Yeh; Jean Kossaifi; Kamyar Azizzadenesheli; Animashree Anandkumar (NeurIPS, 2024)

A Practical Probabilistic Benchmark for AI Weather Models. - Noah D. Brenowitz; Yair Cohen; Jaideep Pathak; Ankur Mahesh; Boris Bonev; Thorsten Kurth; Dale R. Durran; Peter Harrington; Michael S. Pritchard (CoRR, 2024)

Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Model. - Chenggong Wang; Michael S. Pritchard; Noah D. Brenowitz; Yair Cohen; Boris Bonev; Thorsten Kurth; Dale R. Durran; Jaideep Pathak (CoRR, 2024)

Huge Ensembles Part II: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators. - Ankur Mahesh; William D. Collins; Boris Bonev; Noah D. Brenowitz; Yair Cohen; Peter Harrington; Karthik Kashinath; Thorsten Kurth; Joshua North; Travis A. O'Brien; Michael S. Pritchard; David Pruitt; et al. (CoRR, 2024)

Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators. - Ankur Mahesh; William D. Collins; Boris Bonev; Noah D. Brenowitz; Yair Cohen; Joshua Elms; Peter Harrington; Karthik Kashinath; Thorsten Kurth; Joshua North; Travis A. O'Brien; Michael S. Pritchard; et al. (CoRR, 2024)

Exploring the design space of deep-learning-based weather forecasting systems. - Shoaib Ahmed Siddiqui; Jean Kossaifi; Boris Bonev; Christopher B. Choy; Jan Kautz; David Krueger 001; Kamyar Azizzadenesheli (CoRR, 2024)

Modulated Adaptive Fourier Neural Operators for Temporal Interpolation of Weather Forecasts. - Jussi Leinonen; Boris Bonev; Thorsten Kurth; Yair Cohen (CoRR, 2024)

Data-driven Surface Solar Irradiance Estimation using Neural Operators at Global Scale. - Alberto Carpentieri; Jussi Leinonen; Jeff Adie; Boris Bonev; Doris Folini; Farah Hariri (CoRR, 2024)

A Library for Learning Neural Operators. - Jean Kossaifi; Nikola B. Kovachki; Zongyi Li; David Pitt; Miguel Liu-Schiaffini; Robert Joseph George; Boris Bonev; Kamyar Azizzadenesheli; Julius Berner; Anima Anandkumar (CoRR, 2024)

Attention on the Sphere. - Boris Bonev; Max Rietmann; Andrea Paris; Alberto Carpentieri; Thorsten Kurth (CoRR, 2025)

Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning. - Julius Berner; Miguel Liu-Schiaffini; Jean Kossaifi; Valentin Duruisseaux; Boris Bonev; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2025)

FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale. - Boris Bonev; Thorsten Kurth; Ankur Mahesh; Mauro Bisson; Jean Kossaifi; Karthik Kashinath; Anima Anandkumar; William D. Collins; Michael S. Pritchard; Alexander Keller (CoRR, 2025)