Wessel P. Bruinsma

Microsoft (Netherlands) — Netherlands

Computer Science · Physical Sciences

9h-index295citations44works11.82yr avg
OpenAlex↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Gaussian Processes and Bayesian Inference(21), Neural Networks and Applications(7), Machine Learning and Data Classification(7), Meteorological Phenomena and Simulations(6), Adversarial Robustness in Machine Learning(5)

Publications44 total

On the effective resolution of AI weather models
2025Open Access
Accurate and scalable exchange-correlation with deep learning
arXiv (Cornell University)·2025· 3 citedOpen Access
A foundation model for the Earth system
Nature·2025· 75 citedOpen Access
End-to-end data-driven weather prediction
Nature·2025· 32 citedOpen Access
 Xaurora: Advancing subseasonal-to-seasonal forecasting by fine-tuning foundation weather models with spectral consistency 
2025Open Access
On the effective resolution of AI weather prediction models
2025
Approximately Equivariant Neural Processes
arXiv (Cornell University)·2024Open Access
Translation Equivariant Transformer Neural Processes
arXiv (Cornell University)·2024Open Access
Noise-Aware Differentially Private Regression via Meta-Learning
arXiv (Cornell University)·2024Open Access
A Foundation Model for the Earth System
arXiv (Cornell University)·2024· 35 citedOpen Access
Aardvark weather: end-to-end data-driven weather forecasting
arXiv (Cornell University)·2024· 8 citedOpen Access
Noise-Aware Differentially Private Regression via Meta-Learning
2024
Approximately Equivariant Neural Processes
2024
Autoregressive Conditional Neural Processes
arXiv (Cornell University)·2023· 3 citedOpen Access
Environmental sensor placement with convolutional Gaussian neural processes
Environmental Data Science·2023· 18 citedOpen Access
Environmental Sensor Placement with Convolutional Gaussian Neural Processes
arXiv (Cornell University)·2022· 2 citedOpen Access
Sparse Gaussian Process Hyperparameters: Optimize or Integrate?
arXiv (Cornell University)·2022· 2 citedOpen Access
Convolutional Conditional Neural Processes
arXiv (Cornell University)·2022· 5 citedOpen Access
Challenges and Pitfalls of Bayesian Unlearning
arXiv (Cornell University)·2022· 1 citedOpen Access
A Note on the Chernoff Bound for Random Variables in the Unit Interval
arXiv (Cornell University)·2022· 1 citedOpen Access
page 1 of 3Next →

Frequent Co-authors

Richard E. Turner(25), James Requeima(16), Stratis Markou(13), Anna Vaughan(9), Andrew Y. K. Foong(8), J. Scott Hosking(7), Richard E. Turner(6), Tom R. Andersson(5), Jonathan Gordon(5), Matthew Ashman(5), Will Tebbutt(4), Eric Perim(4), David R. Burt(4), Megan Stanley(3), Yann Dubois(3), William Tebbutt(3), Mark Bentum(3), Ioan E. Lager(3), Sjoerd Bosma(3), Robin P. Hes(3)