1 citations · 1 across the 1 of their papers we have counts for
5 papers
NOBLE -- Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models
Luca Ghafourpour, Valentin Duruisseaux, Bahareh Tolooshams +3
Characterizing the cellular properties of neurons is fundamental to understanding their function in the brain. In this quest, the generation of bio-realistic models is central towa…
Ultrasound Lung Aeration Map via Physics-Aware Neural Operators
Jiayun Wang, Oleksii Ostras, Masashi Sode +5
Lung ultrasound is a growing modality in clinics for diagnosing and monitoring acute and chronic lung diseases due to its low cost and accessibility. Lung ultrasound works by emitt…
A Unified Model for Compressed Sensing MRI Across Undersampling Patterns
Armeet Singh Jatyani, Jiayun Wang, Aditi Chandrashekar +4
Compressed Sensing MRI reconstructs images of the body's internal anatomy from undersampled measurements, thereby reducing scan time. Recently, deep learning has shown great potent…
Diffusion State-Guided Projected Gradient for Inverse Problems
Rayhan Zirvi, Bahareh Tolooshams, Anima Anandkumar
Recent advancements in diffusion models have been effective in learning data priors for solving inverse problems. They leverage diffusion sampling steps for inducing a data prior w…
Fourier Neural Operators for Learning Dynamics in Quantum Spin Systems
Freya Shah, Taylor L. Patti, Julius Berner +3
Fourier Neural Operators (FNOs) excel on tasks using functional data, such as those originating from partial differential equations. Such characteristics render them an effective a…