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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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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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10/25/2021
Self-supervised similarity search for large scientific datasets
We present the use of self-supervised learning to explore and exploit la...
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09/30/2021
Mining for strong gravitational lenses with self-supervised learning
We employ self-supervised representation learning to distill information...
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06/23/2021
Fast, high-fidelity Lyman α forests with convolutional neural networks
Full-physics cosmological simulations are powerful tools for studying th...
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01/12/2021
Estimating Galactic Distances From Images Using Self-supervised Representation Learning
We use a contrastive self-supervised learning framework to estimate dist...
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12/24/2020
Self-Supervised Representation Learning for Astronomical Images
Sky surveys are the largest data generators in astronomy, making automat...
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07/25/2020
