3 papers
stat.ML2026
Evaluation of optimisation and Bayesian inference methods for reaction rates in atmospheric chemical mechanisms
Valery Ashu, Wenqing Peng, Zhi-Song Liu +7
Constraining reaction rate coefficients is a central challenge in the development of explicit atmospheric chemical mechanisms, particularly for autoxidation systems where many reac…
cs.LG2025
phepy: Visual benchmarks and improvements for out-of-distribution detectors
Felix Krumbiegel, Juniper Tyree, Michael Boy +2
Applying machine learning to increasingly high-dimensional problems with sparse or biased training data increases the risk that a model is used on inputs outside its training domai…
cs.LG2024
Neural Network Emulator for Atmospheric Chemical ODE
Zhi-Song Liu, Petri Clusius, Michael Boy
Modeling atmospheric chemistry is complex and computationally intense. Given the recent success of Deep neural networks in digital signal processing, we propose a Neural Network Em…