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10/29/2022
Ice Core Dating using Probabilistic Programming
Ice cores record crucial information about past climate. However, before...
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06/18/2021
Combining Pseudo-Point and State Space Approximations for Sum-Separable Gaussian Processes
Gaussian processes (GPs) are important probabilistic tools for inference...
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01/20/2021
Convolutional conditional neural processes for local climate downscaling
A new model is presented for multisite statistical downscaling of temper...
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10/20/2020
Sparse Gaussian Process Variational Autoencoders
Large, multi-dimensional spatio-temporal datasets are omnipresent in mod...
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11/14/2019
Scalable Exact Inference in Multi-Output Gaussian Processes
Multi-output Gaussian processes (MOGPs) leverage the flexibility and int...
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07/17/2019
Zygote: A Differentiable Programming System to Bridge Machine Learning and Scientific Computing
Scientific computing is increasingly incorporating the advancements in m...
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07/17/2019
A Differentiable Programming System to Bridge Machine Learning and Scientific Computing
Scientific computing is increasingly incorporating the advancements in m...
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02/20/2018