933 search results for “machine learning” in the Public website
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History
Life Sciences Artificial Intelligence Data Science
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Siuman Chung
Faculteit der Sociale Wetenschappen
s.chung@fsw.leidenuniv.nl | +31 71 527 3830
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Christine Espin
Faculteit der Sociale Wetenschappen
espinca@fsw.leidenuniv.nl | +31 71 527 6630
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Marit Guda
Faculteit der Sociale Wetenschappen
m.c.guda@fsw.leidenuniv.nl | +31 71 527 6344
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Elise Swart
Faculteit der Sociale Wetenschappen
e.k.swart@fsw.leidenuniv.nl | +31 71 527 2727
- About this minor
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Collaborative learning in higher education: design, implementation and evaluation of group learning activities
The aim of this study was to provide insight into how teachers in higher education can be supported in the design, implementation and evaluation of group assignments by developing a theoretical and evidence-based framework for the design of group assignments.
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Applied statistics as a pillar of data science
Data science is now growing fast in many places, but scholars at Leiden University have been developing data science techniques for a long time already. Thanks to their broad-based expertise, Leiden statisticians are currently combining the achievements in statistics with the latest methods of statistical…
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Data Science
The ability to collect and interpret huge quantities of data has become indispensable to society and academia. Leiden University is a knowledge and expertise centre for data science that places the emphasis on interdisciplinary collaboration and innovation.
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Algorithms for quantum software
Top scientists of three Dutch universities are working on software and systems for quantum computers. Researchers of the Leiden Institute of Advanced Computer Science (LIACS) and the Leiden Institute of Physics (LION) are developing new algorithms to make those super computers work. The coming years,…
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Professional learning: what teachers want to learn
The aim of this thesis was to examine what teachers want to learn themselves. The main research question was: what, how and why teachers want to learn? And does this depend on their years of teaching experience and the school at which they work?
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Exploring deep learning for multimodal understanding
This thesis mainly focuses on multimodal understanding and Visual Question Answering (VQA) via deep learning methods. For technical contributions, this thesis first focuses on improving multimodal fusion schemes via multi-stage vision-language interactions.
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Collaborative learning in conservatoire education: catalyst for innovation
The aim of this research project was to increase understanding of which collaborative learning approaches already exist in conservatoire education, and how implementation of collaborative learning could be supported.
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Increased striatal activity in adolescence benefits learning
Heightened activation of the striatum that adolescents show in response to reward is often associated with risk-taking and negative health consequences. This article in Nature Communications investigates a potential positive side of this heightened activation. It shows that the activity peak in late…
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The Hybrid Intelligence Centre
Hybrid Intelligence (HI) is the combination of human and machine intelligence, expanding human intellect instead of replacing it. HI takes human expertise and intentionality into account when making meaningful decisions and perform appropriate actions, together with ethical, legal and societal values.…
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POST_SIGNATURE
To what extent is creative ownership in contemporary (graphic) design practices changing now that we are co-creating with machines? And can machines have copyrights, too?
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MacBERTh & GysBERT meet socio-linguistics: using machine learning to automate annotation and analysis in historical corpora
Lecture, Sociolinguistics series
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Reinforcement learning
The Reinforcement Learning lab conducts research into Reinforcement Learning and Intelligent Combinatorial Algorithms.
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Language as a time machine
About 90 per cent of Austronesian and Papuan languages are under threat of soon becoming extinct. Marian Klamer is the only professor in the world who researches both these language groups. She records languages before they disappear and sheds new light on the history of Indonesia. Inaugural lecture…
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Ben van Werkhoven
Science
b.j.c.van.werkhoven@liacs.leidenuniv.nl | +31 71 527 2727
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Pingtao Ding
Science
p.ding@biology.leidenuniv.nl | +31 71 527 5306
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Thomas Bäck
Science
t.h.w.baeck@liacs.leidenuniv.nl | +31 71 527 7108
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Blended learning
The programme is also offered in a blended learning version: this is a combination of distance learning and face-to-face learning. Read more information
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By Heritage Quest
Read all papers and other types of publication created by the project.
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Data Science: Computer Science (MSc)
The master's specialisation Data Science: Computer Science at Leiden University provides students thorough knowledge and understanding of statistical and computational aspects of data analysis, including their application in databases, advances in data mining, networks, pattern recognition, and deep…
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Exploring Deep Learning for Intelligent Image Retrieval
This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.
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Computational Network Science Lab
The Leiden Computational Network Science Lab (CNS Lab) researches methods for knowledge discovery from real-world network data.
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Artificial Intelligence (MSc)
The master’s specialisation Artificial Intelligence offers future-oriented topics in computer science with a focus on machine learning, optimization algorithms, and decision support techniques.
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Research in Physics, Classical/Quantum Information (MSc)
This master’s programme combines Physics with Data Science. You will learn how physics has its own tricks to deal with big data and how techniques from machine learning and deep learning can be applied to classical and quantum data. The first focus of attention is on classical data, including data mining,…
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Data science
The majority of scientists, from archaeologists through to zoologists, collect enormous volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics and computer science, we can develop algorithms for analyzing…
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Bayesian uncertainty quantication in complex models
The aim of this project is to determine in which cases uncertainty statements resulting from a Bayesian statistical analysis can be trusted.
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Data Mining and Sports
Collecting data in sports increased in importance the last few years.
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Quantum Lab (aQa)
Quantum computing is a novel paradigm for computation, which is nearing real-world impact with the coming generation of limited, but nonetheless powerful quantum devices.
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Self-directed learning with mobile technology in higher education
Language learners in higher education increasingly conduct out-of-class self-directed learning facilitated by mobile technology. This project aims to explore how university students use mobile technology for their self-directed language learning and investigate factors that influence their self-directed…
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Collaborative learning in teacher education: Intended, implemented and experienced curriculum
How is collaborative learning in teacher education designed and implemented? How do students experience those collaborative learning assignments? What aspects of the design and the implementation lead to which perceived learning outcomes?
- Meet our staff
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Wilfried Admiraal
ICLON
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Dineke Tigelaar
ICLON
dtigelaar@iclon.leidenuniv.nl | +31 71 527 6552
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Beth Lloyd
Faculteit der Sociale Wetenschappen
b.lloyd@fsw.leidenuniv.nl | +31 71 527 2727
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Student engagement in blended learning in higher education
In what way can teachers support and enlarge student engagement in a blended learning context?
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Active Learning Network
The active learning network joins together everyone interested in the subject to move the theme further within Leiden University. The SALTSWAT pilot program researches the ways forward for Leiden University.
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Research
At Leiden University, researchers from all disciplines work together to find answers and design innovations in the field of artificial intelligence.
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University teachers’ learning paths during technological innovation of education
To what extent are university teachers' individual learning paths influenced by their teaching experience, motivation, and conceptions of teaching and learning through educational technology?
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Activating teaching and learning
The active learning ambition is based on the idea that knowledge is more likely to ‘stick’ when students are actively engaged with their learning and research. This active student participation has implications for how we teach: less consumption of knowledge and more efficient use of contact hours.
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Flexible learning pathways
The ambition to have flexible learning pathways is about creating possibilities to improve the content and form of students’ learning process, and to link learning to students’ needs. Students who have access to a flexible range of learning pathways can align their university career with their own personal…
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Statistical Science
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.
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Research project: Unravelling the Rule of Law
While acknowledging prominent legal-philosophical debates, this project proposes a radically different approach to provide insights into the concept of the rule of law.
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Special edition Information Polity
In this special edition of Information Polity there is a focus on the transparency challenges of using algorithms in government in decision-making procedures at the macro-, meso-, and micro-levels.
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Pursuing new anti-cancer therapy as a team
Cancer is the leading cause of death in the Netherlands, and, with over 100 different types of cancer, it’s not a simple disease. Today, skin, breast, lung, prostate and colon cancer are the most diagnosed forms. Therefore, the discovery and development of new drugs has the ability to significantly…
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Why Leiden University?
You gain a strong foundation in computer science, combined with knowledge of machine learning, cognitive science, human-robot interaction. You will learn to develop and program systems based on knowledge of the human brain.