16 citations · 35 across the 15 of their papers we have counts for
7 papers · 1 filter
Universal Spectral Tokenization via Self-Supervised Panchromatic Representation Learning
Jeff Shen, Francois Lanusse, Liam Holden Parker +24
Sequential scientific data span many resolutions and domains, and unifying them into a common representation is a key step toward developing foundation models for the sciences. Ast…
Walrus: A Cross-Domain Foundation Model for Continuum Dynamics
Michael McCabe, Payel Mukhopadhyay, Tanya Marwah +22
Foundation models have transformed machine learning for language and vision, but achieving comparable impact in physical simulation remains a challenge. Data heterogeneity and unst…
AION-1: Omnimodal Foundation Model for Astronomical Sciences
Liam Parker, Francois Lanusse, Jeff Shen +24
While foundation models have shown promise across a variety of fields, astronomy still lacks a unified framework for joint modeling across its highly diverse data modalities. In th…
Multimodal Datasets with Controllable Mutual Information
Raheem Karim Hashmani, Garrett W. Merz, Helen Qu +2
We introduce a framework for generating highly multimodal datasets with explicitly calculable mutual information (MI) between modalities. This enables the construction of benchmark…
Dyads: Artist-Centric, AI-Generated Dance Duets
Zixuan Wang, Luis Zerkowski, Ilya Vidrin +1
Existing AI-generated dance methods primarily train on motion capture data from solo dance performances, but a critical feature of dance in nearly any genre is the interaction of t…
Invisible Strings: Revealing Latent Dancer-to-Dancer Interactions with Graph Neural Networks
Luis Vitor Zerkowski, Zixuan Wang, Ilya Vidrin +1
Dancing in a duet often requires a heightened attunement to one's partner: their orientation in space, their momentum, and the forces they exert on you. Dance artists who work in p…
What's In Your Field? Mapping Scientific Research with Knowledge Graphs and Large Language Models
Abhipsha Das, Nicholas Lourie, Siavash Golkar +1
The scientific literature's exponential growth makes it increasingly challenging to navigate and synthesize knowledge across disciplines. Large language models (LLMs) are powerful…