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08/16/2023
Warped geometric information on the optimisation of Euclidean functions
We consider the fundamental task of optimizing a real-valued function de...
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03/09/2023
Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal Metrics
Stochastic-gradient sampling methods are often used to perform Bayesian ...
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10/19/2022
Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection
Anomaly detection methods identify examples that do not follow the expec...
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10/03/2022
Neural network for determining an asteroid mineral composition from reflectance spectra
Chemical and mineral compositions of asteroids reflect the formation and...
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02/01/2022
Lagrangian Manifold Monte Carlo on Monge Patches
The efficiency of Markov Chain Monte Carlo (MCMC) depends on how the und...
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12/06/2021
Traversing Time with Multi-Resolution Gaussian Process State-Space Models
Gaussian Process state-space models capture complex temporal dependencie...
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12/01/2021
Prior knowledge elicitation: The past, present, and future
Specification of the prior distribution for a Bayesian model is a centra...
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06/28/2020
Mixture of Discrete Normalizing Flows for Variational Inference
Advances in gradient-based inference have made distributional approximat...
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06/01/2020
Multi-scale Cloud Detection in Remote Sensing Images using a Dual Convolutional Neural Network
Semantic segmentation by convolutional neural networks (CNN) has advance...
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02/23/2020
Flexible Prior Elicitation via the Prior Predictive Distribution
The prior distribution for the unknown model parameters plays a crucial ...
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10/27/2019
Prior specification via prior predictive matching: Poisson matrix factorization and beyond
Hyperparameter optimization for machine learning models is typically car...
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09/11/2019
Correcting Predictions for Approximate Bayesian Inference
Bayesian models quantify uncertainty and facilitate optimal decision-mak...
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02/02/2019
Variational Bayesian Decision-making for Continuous Utilities
Bayesian decision theory outlines a rigorous framework for making optima...
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04/19/2017
Importance Sampled Stochastic Optimization for Variational Inference
Variational inference approximates the posterior distribution of a proba...
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11/21/2014
Group Factor Analysis
Factor analysis provides linear factors that describe relationships betw...
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10/02/2014
PinView: Implicit Feedback in Content-Based Image Retrieval
This paper describes PinView, a content-based image retrieval system tha...
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12/20/2013
Group-sparse Embeddings in Collective Matrix Factorization
CMF is a technique for simultaneously learning low-rank representations ...
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10/16/2012
Factorized Multi-Modal Topic Model
Multi-modal data collections, such as corpora of paired images and text ...
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03/15/2012
Bayesian exponential family projections for coupled data sources
Exponential family extensions of principal component analysis (EPCA) hav...
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10/14/2011
