In this dissertation non-parametric Bayesian methods are used in the application of robotic vision.

Promotor: Prof.dr. A.W. van der Vaart

This thesis consists of five chapters on how to construct prediction sets for different types of data and models in a parametric or nonparametric Bayesian paradigm.

This dissertation studies the Asymptotics of Bayesian nonparametric inference for Gaussian linear models.

The aim of this project is to determine in which cases uncertainty statements resulting from a Bayesian statistical analysis can be trusted.

PhD Defence

This dissertation is about Bayesian learning from data. How can humans and computers learn from data?

Nonparametric Bayes for high-dimensional models: contraction, credible sets, computations

Novel methods for understanding key aspects that are essential to the future of Bayesian inference for high- or infinite-dimensional models and data.

The Mathematical Institute is responsible for the research and education in mathematics and statistics at Leiden University.

A common method to solve expensive function evaluation problem is using Bayesian Global Optimization, instead of Evolutionary Algorithms.

This thesis develops statistical methods for the analysis of high dimensional data: high dimensional networks reconstruction (Chapters 1-4), incorporation of prior information in networks reconstruction (Chapters 2-4), incorporation of prior knowledge in genetic association studies (Chapter 3).

Promotor: A.W. van der Vaart

Perform cutting-edge research in the area of the STAR mathematics cluster.

Below you can read about 4 methods of PLATO.

The research programme Statistical Science is concerned with the analysis and interpretation of masses of data, the quantification of uncertainty using probability models, and the development and benchmarking of algorithms and methods with these aims.

The ELS lab @Leiden contributes to the Leiden Law Methods Portal.

The project falls in the context of the EU Thematic Strategy on the Sustainable Use of Natural Resources (COM(2005)670). The Institute for Environment and Resources (IES) of the Joint Research Centre (JRC) has developed three sets of decoupling indicators. Such indicators require the definition of a…

Because we cannot directly ask babies about what they know or what they are thinking about, we must find smart and baby-friendly ways to figure it out! Below you can read about the different methods that we typically use in our studies.

Towards self-regulated learning of speaking skills in foreign languages in secondary schools: an adaptive and practical approach.

Revising your curriculum and writing course guides and block/module guides

Promotor: Prof.dr. K.J. Batenburg

Authoritative and cutting-edge, Bacterial Chromatin: Methods and Protocols aims to be useful as an up-to-date reference work for scholars in the bacterial chromatin field, those entering the field from adjacent research fields, and scientists in the eukaryotic chromatin field.

Promotores: J.C. van Houwelingen, S.A. van de Geer

The programme group Research Methods and Statistics develops and teaches the large majority of methodological courses in all phases of the program Education and Child Studies.

Promotor: R. Tijdeman

Promotor: K.J. Batenburg

Analysis of neuroimaging data requires multiple steps where statistics play a crucial role. The MRI methods research group develops new statistical methods that are accurate, transparent and easy to use.

Cathodic corrosion for producing nanoparticles was (re)discovered when trying to control the electrochemical etching of a scanning tunneling microscopy (STM) tip.

The programme group Research Methods and Statistics offers methodological support in many projects in the field of education and child studies.

Promotor: P.D. Grünwald

The programme group Research Methods and Statistics offers support to researchers from a variety of research projects within Education and Child Studies.

Illustrations of the challenges and rewards of doing and representing interdisciplinary research through the methodological developments of 50 experienced researchers.

Promotor: R.D. Gill, F. Taroni

The research in this thesis is focused on tomographic reconstruction based on two imaging modalities in electron microscopy.

In this work we describe three methods to improve the performance of Quantum Field Theory calculations.

Mining time series is a machine learning subfield that focuses on a particular data structure, where variables are measured over (short or long) periods of time.

The blended flipped classroom is a partially online, partially offline course to teach social science research methods. Online, students watch video lectures, do readings, and complete short exercises to acquire basic knowledge of research methodologies and academic skills.

Promotor: J.P. Abrahams, Co-promotor: T. Grüne

Following their application to system biological models, control theory techniques have further potential to aid in the understanding and application of quantitative systems pharmacology models.

Promotoren: R. Tijdeman, A.K. Lenstra, Co-promotor: H.J.J. te Riele

We are developing biology-driven platforms to measure metabolites based on liquid chromatography-mass spectrometry (LC-MS), gas chromatography-MS (GC-MS), and capillary electrophoresis-MS (CE-MS).

In this work, we attempt to answer the question:

Promotores: M.N. Spijker, J.G. Verwer.

Aad van der Vaart, professor of stochastics at Leiden University, has been awarded the NWO Spinoza Prize for his groundbreaking research in statistics. Van der Vaart conducts fundamental research on models that can help, for instance, to identify genes that play a role in cancer.

PhD Defence

Currently the focus of the project is the development of a tool that utilizes dimensionality reduction techniques in order to analyze and interpret the lexical and phonological variation between different sign languages. Additionally, the application of deep learning techniques for the extraction of…

This thesis is based on five papers on several topics.