YoungStatS
The blog of Young Statisticians Europe (YSE)
machine-learning
A small step to understand Generative Adversarial Networks
Gérard Biau, Benoît Cadre, Maxime Sangnier and Ugo Tanielian
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2021-04-27
In the last decade, there have been spectacular advances on the practical side of machine learning. One of the most impressive may be the success of Generative Adversarial Networks (GANs) for image generation (Goodfellow et al. 2014). State of the art models are capable of producing portraits of…
machine-learning
Analysis of a Two-Layer Neural Network via Displacement Convexity
Adel Javanmard, Marco Mondelli and Andrea Montanari
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2021-03-14
We consider the problem of learning a function defined on a compact domain, using linear combinations of a large number of “bump-like” components (neurons). This idea lies at the core of a variety of methods from two-layer neural networks to kernel regression, to boosting. In general, the resulting…
machine-learning
Machine learning for causal inference that works
Richard Hahn
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2021-01-26
I’ve kindly been invited to share a few words about a recent paper my colleagues and I published in Bayesian Analysis: “Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects”. In that paper, we motivate and describe a method that we call…
statistics
Ensemble Forecasting of the Zika Space-Time Spread with Topological Data Analysis
Marwah Soliman, Vyacheslav Lyubchich and Yulia R. Gel
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2020-10-22
As per the records of the World Health Organization, the first formally reported incidence of Zika virus occurred in Brazil in May 2015. The disease then rapidly spread to other countries in Americas and East Asia, affecting more than 1,000,000 people. Zika virus is primarily transmitted through…