| Type | Title | File | Year | |
|---|---|---|---|---|
| Draft | Narrative and Emotional Structures For Generation Of Short Texts For Advice | 2025 | ||
| Draft | Multiway latent block model for pca tensor decomposition | 2025 | ||
| Draft | Small-area estimation under a nonlinear transformed area-level model | 2024 | ||
| Draft | Family of linear regression mixture models stratified along the outcome | 2023 | ||
| Draft | Sparse and reduced-rank family of generalized regressions with transformation from pca or autoencoder | 2023 | ||
| Book | Linear and Deep Models Basics with Pytorch, Numpy, and Scikit-Learn | 2022 | ||
| Draft | Visualization of generalized mean estimators using auxiliary information in survey sampling: additive case and stratification | 2021 | ||
| Draft | Residual odds ratios from 2x2xk tables | 2021 | ||
| Draft | Latent block principal component analysis for binary tables | 2021 | ||
| Draft | Negative binomial latent block model with generalized constraints | 2024 | ||
| Draft | A brief survey of numerical procedures for empirical likelihood | 2021 | ||
| Journal | Visualization of generalized mean estimators using auxiliary information in survey sampling | 2019 | ||
| Conf | Symmetric Generative Methods and tSNE: A Short Survey | 2018 | ||
| Draft | Probabilistic Elastic Embedding Model: Comparison of Alternative Models | 2018 | ||
| Journal | A simple variance estimator of change for rotating repeated surveys: an application to the European Union Statistics on Income and Living Conditions household surveys | 2016 | ||
| Journal | Generalized topographic block model | 2015 | ||
| Journal | Data visualization via latent variables and mixture models: a brief survey | 2015 | ||
| Journal | Topographic Bernoulli block mixture mapping for binary tables | 2014 | ||
| Draft | Position cluster latent block model for binary tables | 2014 | ||
| Draft | Bayesian Gaussian Topographic Block Model | 2014 | ||
| Draft | Benchmarking a random intercept regression for small areas via additional columns and rows | 2013 | ||
| Report | Best practice recommendations on variance estimation and small area estimation in business surveys | 2013 | ||
| Conf | Nonlinear mapping by constrained co-clustering | 2012 | ||
| Conf | Generative topographic mapping and factor analyzers | 2012 | ||
| Draft | A parameterization via random factor for generative topographic mapping | 2009 | ||
| Conf | Probabilistic Enhanced Mapping with the Generative Tabular Model) | 2009 |
About the author
Rodolphe Priam (1975) has an engineer diploma (1999) in applied statistics and a phD related to data sciences. He is first author, main author or co-author of several communications on model inference in statistics and computer journals. In about 2010-2012, he was research assitant at Soton-uk on surveys during about two years and a half. In 2019-2020, he was hired during one full year as a full time biostatistician engineer in medical statistics for an hospital in a French remote territory. During the thesis and during a few years after, he has served as a Lecturer in French universities for about six years from 2002 to 2004 and 2006 to 2008. He has taught applied statistics, probabilities and computing (statistical inference, queueing theory, langage r, langage java, etc) for more than thirty courses and lectures at universities and engineering schools. In 2024, he is Lecturer and has taught computing sciences (C & Python langages, Ubuntu OS in brief, Optimization in brief) and statistical data analysis (Descriptive, Regression, PCA, Tests).