
Stochastic Aggregation in Graph Neural Networks
Graph neural networks (GNNs) manifest pathologies including oversmoothi...
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Variational AutoRegressive Gaussian Processes for Continual Learning
This paper proposes Variational AutoRegressive Gaussian Process (VARGP...
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Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights
Probabilistic neural networks are typically modeled with independent wei...
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Generalized Hidden Parameter MDPs Transferable Modelbased RL in a Handful of Trials
There is broad interest in creating RL agents that can solve many (relat...
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Applying SVGD to Bayesian Neural Networks for Cyclical TimeSeries Prediction and Inference
A regressionbased BNN model is proposed to predict spatiotemporal quant...
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Efficient transfer learning and online adaptation with latent variable models for continuous control
Traditional modelbased RL relies on handspecified or learned models of...
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Pyro: Deep Universal Probabilistic Programming
Pyro is a probabilistic programming language built on Python as a platfo...
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Probabilistic MetaRepresentations Of Neural Networks
Existing Bayesian treatments of neural networks are typically characteri...
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Pathwise Derivatives for Multivariate Distributions
We exploit the link between the transport equation and derivatives of ex...
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Likelihoodfree inference with emulator networks
Approximate Bayesian Computation (ABC) provides methods for Bayesian inf...
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Adversarial Message Passing For Graphical Models
Bayesian inference on structured models typically relies on the ability ...
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Conditional Similarity Networks
What makes images similar? To measure the similarity between images, the...
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Knowledge Transfer with Medical Language Embeddings
Identifying relationships between concepts is a key aspect of scientific...
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A Generative Model of Words and Relationships from Multiple Sources
Neural language models are a powerful tool to embed words into semantic ...
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Bayesian representation learning with oracle constraints
Representation learning systems typically rely on massive amounts of lab...
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Automatic Relevance Determination For Deep Generative Models
A recurring problem when building probabilistic latent variable models i...
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Theofanis Karaletsos
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