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09/06/2023
Generalised Mutual Information: a Framework for Discriminative Clustering
In the last decade, recent successes in deep clustering majorly involved...
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04/17/2023
Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models
Federated learning allows for the training of machine learning models on...
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02/15/2023
Are labels informative in semi-supervised learning? – Estimating and leveraging the missing-data mechanism
Semi-supervised learning is a powerful technique for leveraging unlabele...
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02/07/2023
Sparse GEMINI for Joint Discriminative Clustering and Feature Selection
Feature selection in clustering is a hard task which involves simultaneo...
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12/06/2022
Explainability as statistical inference
A wide variety of model explanation approaches have been proposed in rec...
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10/12/2022
Generalised Mutual Information for Discriminative Clustering
In the last decade, recent successes in deep clustering majorly involved...
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05/02/2022
A Multi-stage deep architecture for summary generation of soccer videos
Video content is present in an ever-increasing number of fields, both sc...
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03/14/2022
Don't fear the unlabelled: safe deep semi-supervised learning via simple debiasing
Semi supervised learning (SSL) provides an effective means of leveraging...
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03/02/2022
Model-agnostic out-of-distribution detection using combined statistical tests
We present simple methods for out-of-distribution detection using a trai...
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01/26/2022
Uphill Roads to Variational Tightness: Monotonicity and Monte Carlo Objectives
We revisit the theory of importance weighted variational inference (IWVI...
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06/01/2021
Tensor decomposition for learning Gaussian mixtures from moments
In data processing and machine learning, an important challenge is to re...
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02/03/2021
Unobserved classes and extra variables in high-dimensional discriminant analysis
In supervised classification problems, the test set may contain data poi...
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06/23/2020
not-MIWAE: Deep Generative Modelling with Missing not at Random Data
When a missing process depends on the missing values themselves, it need...
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02/14/2019
A Parsimonious Tour of Bayesian Model Uncertainty
Modern statistical software and machine learning libraries are enabling ...
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01/29/2019
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
We present a novel family of deep neural architectures, named partially ...
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12/06/2018
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data
We consider the problem of handling missing data with deep latent variab...
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12/06/2018
missIWAE: Deep Generative Modelling and Imputation of Incomplete Data
We present a simple technique to train deep latent variable models (DLVM...
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02/13/2018
Leveraging the Exact Likelihood of Deep Latent Variable Models
Deep latent variable models combine the approximation abilities of deep ...
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02/13/2018
Leveraging the Exact Likelihood of Deep Latent Variables Models
Deep latent variable models combine the approximation abilities of deep ...
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03/08/2017
Exact Dimensionality Selection for Bayesian PCA
We present a Bayesian model selection approach to estimate the intrinsic...
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05/19/2016