
On the Benefits of Invariance in Neural Networks
Many real world data analysis problems exhibit invariant structure, and ...
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Probabilistic symmetry and invariant neural networks
In an effort to improve the performance of deep neural networks in data...
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Sequential sampling of Gaussian process latent variable models
We consider the problem of inferring a latent function in a probabilisti...
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Sequential sampling of Gaussian latent variable models
We consider the problem of inferring a latent function in a probabilisti...
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Sampling and Inference for Beta NeutraltotheLeft Models of Sparse Networks
Empirical evidence suggests that heavytailed degree distributions occur...
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Random Walk Models of Network Formation and Sequential Monte Carlo Methods for Graphs
We introduce a class of network models that insert edges by connecting t...
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Benjamin BloemReddy
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