Micah Bowles — accepted AI-conference papers

2025

AION-1: Omnimodal Foundation Model for Astronomical Sciences

Liam Holden Parker, Francois Lanusse, Jeff Shen, Ollie Liu, Tom Hehir, Leopoldo Sarra +19

NeurIPS 2025poster

While foundation models have shown promise across a variety of fields, astronomy lacks a unified framework for joint modeling across its highly diverse data modalities. In this paper, we present AION-1, the first large-scale multimodal foundation family of models for astronomy. AION-1 enables arbitr…

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2024

The Multimodal Universe: Enabling Large-Scale Machine Learning with 100 TB of Astronomical Scientific Data

Eirini Angeloudi, Jeroen Audenaert, Micah Bowles, Benjamin M. Boyd, David Chemaly, Brian Cherinka +23

NeurIPS 2024poster

We present the `Multimodal Universe`, a large-scale multimodal dataset of scientific astronomical data, compiled specifically to facilitate machine learning research. Overall, our dataset contains hundreds of millions of astronomical observations, constituting 100TB of multi-channel and hyper-spectr…

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