
Physicsbased machine learning for modeling stochastic IP3dependent calcium dynamics
We present a machine learning method for model reduction which incorpora...
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Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis
We present a method for learning "spectrally descriptive" edge weights f...
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Graph Prolongation Convolutional Networks: Explicitly Multiscale Machine Learning on Graphs, with Applications to Modeling of Biological Systems
We define a novel type of ensemble Graph Convolutional Network (GCN) mod...
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Novel diffusionderived distance measures for graphs
We define a new family of similarity and distance measures on graphs, an...
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Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions
The moments of spatial probabilistic systems are often given by an infin...
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Multilevel Artificial Neural Network Training for Spatially Correlated Learning
Multigrid modeling algorithms are a technique used to accelerate relaxat...
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Prospects for Declarative Mathematical Modeling of Complex Biological Systems
Declarative modeling uses symbolic expressions to represent models. With...
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Compositional Stochastic Modeling and Probabilistic Programming
Probabilistic programming is related to a compositional approach to stoc...
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Eric Mjolsness
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