Philip Stier

According to our database, Philip Stier authored at least 8 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Lossy Neural Compression for Geospatial Analytics: A Review.

Carlos Gomes, Isabelle Wittmann, Damien Robert, Johannes Jakubik, Tim Reichelt, Michele Martone, Stefano Maurogiovanni, Rikard Vinge, Jonas Hurst, Erik Scheurer, Rocco Sedona, Thomas Brunschwiler, Stefan Kesselheim, Matej Batic, Philip Stier, Jan Dirk Wegner, Gabriele Cavallaro, Edzer Pebesma, Michael Marszalek, Miguel Angel Belenguer-Plomer, Kennedy Adriko, Paolo Fraccaro, Romeo Kienzler, Rania Briq, Sabrina Benassou, Michele Lazzarini, Conrad M. Albrecht

CoRR, March, 2025

Invertible Neural Networks for Probabilistic Aerosol Optical Depth Retrieval.

Paolo Pelucchi, Jorge Vicent Servera, Philip Stier, Gustau Camps-Valls

IEEE Trans. Geosci. Remote. Sens., 2025

2022

Physics-Informed Learning of Aerosol Microphysics.

Paula Harder, Duncan Watson-Parris, Philip Stier, Dominik Strassel, Nicolas R. Gauger, Janis Keuper

CoRR, 2022

Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions.

Andrew Jesson, Alyson Douglas, Peter Manshausen, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit

CoRR, 2022

Scalable Sensitivity and Uncertainty Analyses for Causal-Effect Estimates of Continuous-Valued Interventions.

Andrew Jesson, Alyson Douglas, Peter Manshausen, Maëlys Solal, Nicolai Meinshausen, Philip Stier, Yarin Gal, Uri Shalit

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific.

Andrew Jesson, Peter Manshausen, Alyson Douglas, Duncan Watson-Parris, Yarin Gal, Philip Stier

CoRR, 2021

Emulating Aerosol Microphysics with Machine Learning.

Paula Harder, Duncan Watson-Parris, Dominik Strassel, Nicolas R. Gauger, Philip Stier, Janis Keuper

CoRR, 2021

2019

Detecting anthropogenic cloud perturbations with deep learning.

Duncan Watson-Parris, Samuel Sutherland, Matthew Christensen, Anthony L. Caterini, Dino Sejdinovic, Philip Stier

CoRR, 2019