activity
20242026
most citedEnhancing 3D Planetary Atmosphere Simulations with a Surrogate Radiative Transfer Model

7 citations · 13 across the 7 of their papers we have counts for

collaborators

8 papers

astro-ph.IM2026

Graph neural networks for exoplanet atmospheres

Antonia Vojtekova, Kai Hou Yip, Ingo P. Waldmann +4

Calculating disequilibrium chemistry in exoplanet atmospheres remains a significant computational bottleneck in atmospheric retrievals. The increasing observational precision from…

astro-ph.EP2026

A public dataset of Ariel simulated observations for developing exoplanetary atmosphere data reduction pipelines

Lorenzo V. Mugnai, Kai Hou Yip, Andrea Bocchieri +7

Detecting and characterising exoplanet atmospheres remains challenging because atmospheric signals can be comparable to residual noise and instrumental/astrophysical systematics. S…

physics.comp-ph2025

Adaptive Online Emulation for Accelerating Complex Physical Simulations

Tara P. A. Tahseen, Nikolaos Nikolaou, Luís F. Simões +3

Complex physical simulations often require trade-offs between model fidelity and computational feasibility. We introduce Adaptive Online Emulation (AOE), which dynamically learns n…

astro-ph.EP2025

Investigating the Influence of Asymmetric Errors on Retrievals of Exoplanet Transmission Spectra

Jack J. Davey, Kai Hou Yip, Quentin Changeat +1

In studies of exoplanet atmospheres using transmission spectroscopy, Bayesian retrievals are the most popular form of analysis. In these procedures it is common to adopt a Gaussian…

astro-ph.EP2025

Extreme Learning Machines for Exoplanet Simulations: A Faster, Lightweight Alternative to Deep Learning

Tara P. A. Tahseen, Luís F. Simões, Kai Hou Yip +3

Increasing resolution and coverage of astrophysical and climate data necessitates increasingly sophisticated models, often pushing the limits of computational feasibility. While em…

cs.LG2024

Operational range bounding of spectroscopy models with anomaly detection

Luís F. Simões, Pierluigi Casale, Marília Felismino +4

Safe operation of machine learning models requires architectures that explicitly delimit their operational ranges. We evaluate the ability of anomaly detection algorithms to provid…

astro-ph.EP2024★ 6 cited

The effect of spectroscopic binning on atmospheric retrievals

Jack J. Davey, Kai Hou Yip, Ahmed F. Al-Refaie +1

With the JWST offering higher resolution data in space-based transmission spectroscopy, understanding the capabilities of our current atmospheric retrieval pipelines is essential.…

astro-ph.EP2024★ 7 cited

Enhancing 3D Planetary Atmosphere Simulations with a Surrogate Radiative Transfer Model

Tara P. A. Tahseen, João M. Mendonça, Kai Hou Yip +1

This work introduces an approach to enhancing the computational efficiency of 3D atmospheric simulations by integrating a machine-learned surrogate model into the OASIS global circ…