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05/30/2023
Contextual Vision Transformers for Robust Representation Learning
We present Contextual Vision Transformers (ContextViT), a method for pro...
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11/04/2022
Black-box Coreset Variational Inference
Recent advances in coreset methods have shown that a selection of repres...
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10/01/2021
TyXe: Pyro-based Bayesian neural nets for Pytorch
We introduce TyXe, a Bayesian neural network library built on top of Pyt...
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06/17/2021
Localized Uncertainty Attacks
The susceptibility of deep learning models to adversarial perturbations ...
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02/25/2021
Stochastic Aggregation in Graph Neural Networks
Graph neural networks (GNNs) manifest pathologies including over-smoothi...
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06/09/2020
Variational Auto-Regressive Gaussian Processes for Continual Learning
This paper proposes Variational Auto-Regressive Gaussian Process (VAR-GP...
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02/10/2020
Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights
Probabilistic neural networks are typically modeled with independent wei...
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02/08/2020
Generalized Hidden Parameter MDPs Transferable Model-based RL in a Handful of Trials
There is broad interest in creating RL agents that can solve many (relat...
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01/17/2019
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference
A regression-based BNN model is proposed to predict spatiotemporal quant...
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12/08/2018
Efficient transfer learning and online adaptation with latent variable models for continuous control
Traditional model-based RL relies on hand-specified or learned models of...
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10/18/2018
Pyro: Deep Universal Probabilistic Programming
Pyro is a probabilistic programming language built on Python as a platfo...
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10/01/2018
Probabilistic Meta-Representations Of Neural Networks
Existing Bayesian treatments of neural networks are typically characteri...
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06/05/2018
Pathwise Derivatives for Multivariate Distributions
We exploit the link between the transport equation and derivatives of ex...
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05/23/2018
Likelihood-free inference with emulator networks
Approximate Bayesian Computation (ABC) provides methods for Bayesian inf...
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12/15/2016
Adversarial Message Passing For Graphical Models
Bayesian inference on structured models typically relies on the ability ...
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03/25/2016
Conditional Similarity Networks
What makes images similar? To measure the similarity between images, the...
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02/10/2016
Knowledge Transfer with Medical Language Embeddings
Identifying relationships between concepts is a key aspect of scientific...
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10/01/2015
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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06/16/2015
Bayesian representation learning with oracle constraints
Representation learning systems typically rely on massive amounts of lab...
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05/28/2015