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01/19/2023
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs
U-Net architectures are ubiquitous in state-of-the-art deep learning, ho...
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06/09/2021
Multi-Facet Clustering Variational Autoencoders
Work in deep clustering focuses on finding a single partition of data. H...
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06/25/2020
Neural Decomposition: Functional ANOVA with Variational Autoencoders
Variational Autoencoders (VAEs) have become a popular approach for dimen...
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03/06/2020
BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders
Variational Autoencoders (VAEs) provide a flexible and scalable framewor...
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06/28/2019
Bayesian Nonparametric Boolean Factor Models
We build upon probabilistic models for Boolean Matrix and Boolean Tensor...
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10/16/2018
Covariate Gaussian Process Latent Variable Models
Gaussian Process Regression (GPR) and Gaussian Process Latent Variable M...
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05/11/2018
TensOrMachine: Probabilistic Boolean Tensor Decomposition
Boolean tensor decomposition approximates data of multi-way binary relat...
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03/24/2017
Rejection-free Ensemble MCMC with applications to Factorial Hidden Markov Models
Bayesian inference for complex models is challenging due to the need to ...
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03/22/2017
Testing and Learning on Distributions with Symmetric Noise Invariance
Kernel embeddings of distributions and the Maximum Mean Discrepancy (MMD...
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02/20/2017
Bayesian Boolean Matrix Factorisation
Boolean matrix factorisation aims to decompose a binary data matrix into...
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10/27/2016