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06/18/2023
Towards Stability of Autoregressive Neural Operators
Neural operators have proven to be a promising approach for modeling spa...
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06/01/2023
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior
Pre-trained machine learning (ML) models have shown great performance fo...
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10/22/2022
Generative Modeling of High-resolution Global Precipitation Forecasts
Forecasting global precipitation patterns and, in particular, extreme pr...
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08/08/2022
FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operators
Extreme weather amplified by climate change is causing increasingly deva...
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07/08/2022
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks
Physics-informed neural networks (PINNs) incorporate physical knowledge ...
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02/22/2022
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
FourCastNet, short for Fourier Forecasting Neural Network, is a global d...
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06/10/2021
Ensemble inversion for brain tumor growth models with mass effect
We propose a method for extracting physics-based biomarkers from a singl...
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02/24/2021
Quantitative in vivo imaging to enable tumor forecasting and treatment optimization
Current clinical decision-making in oncology relies on averages of large...
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06/17/2020
Multiatlas Calibration of Biophysical Brain Tumor Growth Models with Mass Effect
We present a 3D fully-automatic method for the calibration of partial di...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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10/11/2018