Alex Bihlo - RankMe

23 papers Journal 23

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Diffeomorphic Neural Operator Learning. CoRR Seth Taylor, Alex Bihlo, Jean-Christophe Nave
2025	J	`jnl`	Exactly conservative physics-informed neural networks and deep operator networks for dynamical systems. Neural Networks Elsa Dos Cardoso-Bihlo, Alex Bihlo
2025	J	`jnl`	ForeCite: Adapting Pre-Trained Language Models to Predict Future Citation Rates of Academic Papers. CoRR Gavin Hull, Alex Bihlo
2025	J	`jnl`	Learning vertical coordinates via automatic differentiation of a dynamical core. CoRR Tim Whittaker, Seth Taylor, Elsa Dos Cardoso-Bihlo, Alejandro Di Luca, Alex Bihlo
2025	J	`jnl`	Low-rank adaptive physics-informed HyperDeepONets for solving differential equations. CoRR Etienne Zeudong, Elsa Dos Cardoso-Bihlo, Alex Bihlo
2025	J	`jnl`	Mapping Galaxy Images Across Ultraviolet, Visible and Infrared Bands Using Generative Deep Learning. CoRR Youssef Zaazou, Alex Bihlo, Terrence S. Tricco
2025	J	`jnl`	Physics-informed neural networks for tsunami inundation modeling. J. Comput. Phys. Rüdiger Brecht, Elsa Dos Cardoso-Bihlo, Alex Bihlo
2024	J	`jnl`	Improving physics-informed neural networks with meta-learned optimization. J. Mach. Learn. Res. Alex Bihlo
2024	J	`jnl`	Invariant Physics-Informed Neural Networks for Ordinary Differential Equations. J. Mach. Learn. Res. Shivam Arora, Alex Bihlo, Francis Valiquette
2024	J	`jnl`	PinnDE: Physics-Informed Neural Networks for Solving Differential Equations. CoRR Jason Matthews, Alex Bihlo
2023	J	`jnl`	Exactly conservative physics-informed neural networks and deep operator networks for dynamical systems. CoRR Elsa Dos Cardoso-Bihlo, Alex Bihlo
2023	J	`jnl`	Improving physics-informed DeepONets with hard constraints. CoRR Rüdiger Brecht, Dmytro R. Popovych, Alex Bihlo, Roman O. Popovych
2023	J	`jnl`	Improving physics-informed neural networks with meta-learned optimization. CoRR Alex Bihlo
2023	J	`jnl`	M-ENIAC: A machine learning recreation of the first successful numerical weather forecasts. CoRR Rüdiger Brecht, Alex Bihlo
2023	J	`jnl`	Model-agnostic machine learning of conservation laws from data. CoRR Shivam Arora, Alex Bihlo, Rüdiger Brecht, Pavel Holba
2023	J	`jnl`	Towards replacing precipitation ensemble predictions systems using machine learning. CoRR Rüdiger Brecht, Alex Bihlo
2022	J	`jnl`	Computing the ensemble spread from deterministic weather predictions using conditional generative adversarial networks. CoRR Rüdiger Brecht, Alex Bihlo
2022	J	`jnl`	Improving trajectory calculations using deep learning inspired single image superresolution. CoRR Rüdiger Brecht, Lucie Bakels, Alex Bihlo, Andreas Stohl
2022	J	`jnl`	Physics-informed neural networks for the shallow-water equations on the sphere. J. Comput. Phys. Alex Bihlo, Roman O. Popovych
2021	J	`jnl`	A generative adversarial network approach to (ensemble) weather prediction. Neural Networks Alex Bihlo
2021	J	`jnl`	Invariant Variational Schemes for Ordinary Differential Equations. CoRR Alex Bihlo, James Jackaman, Francis Valiquette
2021	J	`jnl`	Physics-informed neural networks for the shallow-water equations on the sphere. CoRR Alex Bihlo, Roman O. Popovych
2019	J	`jnl`	On the development of symmetry-preserving finite element schemes for ordinary differential equations. CoRR Alex Bihlo, James Jackaman, Francis Valiquette