22 citations · 55 across the 16 of their papers we have counts for
6 papers · 1 filter
The exact LCU sampling overhead of collective diagonal unitaries: resonances and a continued-fraction dichotomy
Zhihui Wang, Sujit Roy, Manil Maskey +1
The minimal sampling overhead of the quadratic collective phase over one layer of single-qubit rotations is decided by the continued fraction of . Here is a c…
Structured Quantum Kernels for Chaotic Forecasting
Zhihui Wang, Sujit Roy, Ata Akbari +2
Quantum kernels promise exponentially large feature spaces, but expressive circuits render their Gram matrices uninformative, bandwidth tuning collapses them toward classical RBF,…
Multimodal-Multiresolution Foundation Model for Lunar Remote Sensing
Paolo Fraccaro, Gabby Nyirjesy, Daniela Szwarcman +19
We present a multimodal foundation model for lunar remote sensing, pretrained from scratch on SomBench, a geographically partitioned corpus of nearly two million co-registered tile…
SomBench: Benchmark Dataset for Advancing Machine Learning in Lunar Science
Himanshu Patil, Gabby Nyirjesy, Rachel A. Slank +19
Lunar orbital missions, such as Lunar Reconnaissance Orbiter, Kaguya/SELENE, Gravity Recovery and Interior Laboratory, and Lunar Prospector, among others, provide rich multi-instru…
Prithvi-Precip: Integrating Satellite Observations into an Atmospheric AI Foundation Model for Precipitation Forecasting
Simon Pfreundschuh, Christian D. Kummerow, Johannes Schmude +5
Accurate precipitation forecasting remains one of the most challenging problems in weather prediction. While recent AI weather prediction (AIWP) systems have achieved substantial i…
PDE foundation models are skillful AI weather emulators for the Martian atmosphere
Johannes Schmude, Sujit Roy, Liping Wang +10
We show that AI foundation models that are pretrained on numerical solutions to a diverse corpus of partial differential equations can be adapted and fine-tuned to obtain skillful…