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01/31/2023
The passive symmetries of machine learning
Any representation of data involves arbitrary investigator choices. Beca...
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04/02/2022
Dimensionless machine learning: Imposing exact units equivariance
Units equivariance is the exact symmetry that follows from the requireme...
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10/07/2021
A simple equivariant machine learning method for dynamics based on scalars
Physical systems obey strict symmetry principles. We expect that machine...
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06/11/2021
Scalars are universal: Gauge-equivariant machine learning, structured like classical physics
There has been enormous progress in the last few years in designing conc...
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03/01/2021
Dynamic estimation with random forests for discrete-time survival data
Time-varying covariates are often available in survival studies and esti...
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05/31/2020
Ensemble Methods for Survival Data with Time-Varying Covariates
We propose two new survival forests for survival data with time-varying ...
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08/15/2019
Experimental performance of graph neural networks on random instances of max-cut
This note explores the applicability of unsupervised machine learning te...
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01/14/2019
