Björn Lütjens

29 papers A* 4Misc 1Journal 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	PDE foundation models are skillful AI weather emulators for the Martian atmosphere. CoRR Johannes Schmude, Sujit Roy, Liping Wang, Theodore van Kessel, Levente J. Klein, Marcus Freitag, Eloisa Bentivegna, Robert Manson-Sawko, Björn Lütjens, Manil Maskey, Campbell D. Watson, Rahul Ramachandran, Juan Bernabé-Moreno
2025	J	`jnl`	ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation. J. Mach. Learn. Res. Sungduk Yu, Zeyuan Hu, Akshay Subramaniam, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius J. M. Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Helge Heuer, Benjamin R. Hillman, Andrea M. Jenney, Nana Liu, Alistair White, Tian Zheng, Zhiming Kuang, Fiaz Ahmed, Elizabeth A. Barnes, Noah D. Brenowitz, Christopher S. Bretherton, Veronika Eyring, Savannah L. Ferretti, Nicholas J. Lutsko, Pierre Gentine, Stephan Mandt, J. David Neelin, Rose Yu, Laure Zanna, Nathan M. Urban, Janni Yuval, Ryan Abernathey, Pierre Baldi, Wayne Chuang, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Po-Lun Ma, Sara Shamekh, Guang Zhang, Michael S. Pritchard
2025	J	`jnl`	MeltwaterBench: Deep learning for spatiotemporal downscaling of surface meltwater. CoRR Björn Lütjens, Patrick Alexander, Raf Antwerpen, Til Widmann, Guido Cervone, Marco Tedesco
2024	J	`jnl`	Generating Physically-Consistent Satellite Imagery for Climate Visualizations. IEEE Trans. Geosci. Remote. Sens. Björn Lütjens, Brandon Leshchinskiy, Océane Boulais, Farrukh Chishtie, Natalia Díaz Rodríguez, Margaux Masson-Forsythe, Ana Mata-Payerro, Christian Requena-Mesa, Aruna Sankaranarayanan, Aaron Piña, Yarin Gal, Chedy Raïssi, Alexander Lavin, Dava J. Newman
2024	J	`jnl`	The impact of internal variability on benchmarking deep learning climate emulators. CoRR Björn Lütjens, Raffaele Ferrari, Duncan Watson-Parris, Noelle Selin
2023	A*	`conf`	ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard
2023	J	`jnl`	ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. CoRR Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.
2023	A*	`conf`	GEO-Bench: Toward Foundation Models for Earth Monitoring. NeurIPS Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan D. Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava J. Newman, Yoshua Bengio, Stefano Ermon, Xiaoxiang Zhu
2023	J	`jnl`	GEO-Bench: Toward Foundation Models for Earth Monitoring. CoRR Alexandre Lacoste, Nils Lehmann, Pau Rodríguez, Evan David Sherwin, Hannah Kerner, Björn Lütjens, Jeremy Andrew Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vázquez, Dava J. Newman, Yoshua Bengio, Stefano Ermon, Xiao Xiang Zhu
2023	J	`jnl`	Teaching Computer Vision for Ecology. CoRR Elijah Cole, Suzanne Stathatos, Björn Lütjens, Tarun Sharma, Justin Kay, Jason R. Parham, Benjamin Kellenberger, Sara Beery
2022	J	`jnl`	Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning. IEEE Trans. Neural Networks Learn. Syst. Michael Everett, Björn Lütjens, Jonathan P. How
2022	J	`jnl`	Multiscale Neural Operator: Learning Fast and Grid-independent PDE Solvers. CoRR Björn Lütjens, Catherine H. Crawford, Campbell D. Watson, Christopher Hill, Dava J. Newman
2022	A*	`conf`	ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery. AAAI Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Kenza Amara, Attila Steinegger, Ce Zhang, Xiaoxiang Zhu
2022	J	`jnl`	ReforesTree: A Dataset for Estimating Tropical Forest Carbon Stock with Deep Learning and Aerial Imagery. CoRR Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Kenza Amara, Attila Steinegger, Ce Zhang, Xiaoxiang Zhu
2021	J	`jnl`	PCE-PINNs: Physics-Informed Neural Networks for Uncertainty Propagation in Ocean Modeling. CoRR Björn Lütjens, Catherine H. Crawford, Mark Veillette, Dava J. Newman
2021	J	`jnl`	Physically-Consistent Generative Adversarial Networks for Coastal Flood Visualization. CoRR Björn Lütjens, Brandon Leshchinskiy, Christian Requena-Mesa, Farrukh Chishtie, Natalia Díaz Rodríguez, Océane Boulais, Aruna Sankaranarayanan, Aaron Piña, Yarin Gal, Chedy Raïssi, Alexander Lavin, Dava J. Newman
2021	J	`jnl`	Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery. CoRR Gyri Reiersen, David Dao, Björn Lütjens, Konstantin Klemmer, Xiaoxiang Zhu, Ce Zhang
2021	J	`jnl`	The World as a Graph: Improving El Niño Forecasts with Graph Neural Networks. CoRR Salva Rühling Cachay, Emma Erickson, Arthur Fender C. Bucker, Ernest Pokropek, Willa Potosnak, Suyash Bire, Salomey Osei, Björn Lütjens
2021	J	`jnl`	Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark. CoRR Alexandre Lacoste, Evan David Sherwin, Hannah Kerner, Hamed Alemohammad, Björn Lütjens, Jeremy Irvin, David Dao, Alex Chang, Mehmet Gunturkun, Alexandre Drouin, Pau Rodríguez, David Vázquez
2021	J	`jnl`	WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data. CoRR Rupa Kurinchi-Vendhan, Björn Lütjens, Ritwik Gupta, Lucien Werner, Dava J. Newman
2020	J	`jnl`	Certified Adversarial Robustness for Deep Reinforcement Learning. CoRR Michael Everett, Björn Lütjens, Jonathan P. How
2020	J	`jnl`	Graph Neural Networks for Improved El Niño Forecasting. CoRR Salva Rühling Cachay, Emma Erickson, Arthur Fender C. Bucker, Ernest Pokropek, Willa Potosnak, Salomey Osei, Björn Lütjens
2020	J	`jnl`	Physics-informed GANs for Coastal Flood Visualization. CoRR Björn Lütjens, Brandon Leshchinskiy, Christian Requena-Mesa, Farrukh Chishtie, Natalia Díaz Rodríguez, Océane Boulais, Aaron Piña, Dava J. Newman, Alexander Lavin, Yarin Gal, Chedy Raïssi
2020	J	`jnl`	TrueBranch: Metric Learning-based Verification of Forest Conservation Projects. CoRR Simona Santamaria, David Dao, Björn Lütjens, Ce Zhang
2019	Misc	`conf`	Certified Adversarial Robustness for Deep Reinforcement Learning. CoRL Björn Lütjens, Michael Everett, Jonathan P. How
2019	J	`jnl`	Certified Adversarial Robustness for Deep Reinforcement Learning. CoRR Björn Lütjens, Michael Everett, Jonathan P. How
2019	J	`jnl`	Machine Learning-based Estimation of Forest Carbon Stocks to increase Transparency of Forest Preservation Efforts. CoRR Björn Lütjens, Lucas Liebenwein, Katharina Kramer
2019	A*	`conf`	Safe Reinforcement Learning With Model Uncertainty Estimates. ICRA Björn Lütjens, Michael Everett, Jonathan P. How
2018	J	`jnl`	Safe Reinforcement Learning with Model Uncertainty Estimates. CoRR Björn Lütjens, Michael Everett, Jonathan P. How