750 search results for “gravitational learning” in the Public website
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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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Machine Learning
Computers are capable of making incredibly accurate predictions on the basis of machine learning. In other words, these computers can learn without intervention once they have been pre-programmed by humans. At LIACS, we explore and push the borders of what a revolutionary new generation of algorithms…
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Michael LewFaculty of Science
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NWO Gravitation Programme awarded 10-year grant to research consortia 'Networks'
Professor Frank den Hollander has been awarded a 10-year grant through the NWO Gravitation program, jointly with colleagues from the University of Amsterdam, the Center for Mathematics and Computer Science in Amsterdam, and the Technical University of Eindhoven.
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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?
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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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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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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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Mart MojetICLON
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Sietse SchröderFaculty of Science
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Chloe HongICLON
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Xiaomei WeiICLON
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Frans RodenburgFaculty of Science
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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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Efficient tuning of automated machine learning pipelines
Automated Machine Learning (AutoML) is widely used to automatically build a suitable practical Machine Learning (ML) model for an arbitrary real-world problem, reducing the effort of practitioners in the ML development cycle for real-world applications. Optimization is a key part of a typical AutoML…
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Learning objectives
After this course, you will
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Learning from small samples
Learning from small data sets in machine learning is a crucial challenge, especially when dealing with data imbalances and anomaly detection. This thesis delves into the challenges and methodologies of learning from small datasets in machine learning, with a particular focus on addressing data imbalances…
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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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Wouter van LoonSocial & Behavioural Sciences
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Object-based learning in science museums
How do museum visitors interpret the authenticity of museum objects? How can we support visitors' meaningful interactions with real objects?
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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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Machine learning and computer vision for urban drainage inspections
Sewer pipes are an essential infrastructure in modern society and their proper operation is important for public health. To keep sewer pipes operational as much as possible, periodical inspections for defects are performed.
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Aggravating matters: accounting for baryons in cosmological analyses
Three major cosmology-focused missions are planned for the next decade: the Euclid space telescope, the Vera C. Rubin Observatory in Chile, and the Nancy Grace Roman Space Telescope.
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Centre for Professional Learning
The Centre for Professional Learning (CPL) develops in-depth and challenging programmes for higher educated professionals.
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Elise SwartSocial & Behavioural Sciences
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Kim Stroet
Social & Behavioural Sciences
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Mario de JongeICLON
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Simon Portegies ZwartFaculty of Science
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Language Learning Resource Centre
The language learning resource centre unites all language teaching professionals working at Leiden University: teachers and researchers at the LUCL, ATC, LUCAS, LIAS, and ICLON.
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Professional learning
Would you like to develop further and be challenged academically in your field or beyond? The Faculty of Humanities offers a wide range of courses to boost your career, learn new skills or broaden your knowledge.
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Marga HarmantoICLON
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Emma EveraertSocial & Behavioural Sciences
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Geerte Holwerda-van den BergICLON
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Leiden Learning & Innovation Centre
LLInC supports innovative and high-quality education, within Leiden University and in partnership with academic and social organisations.
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Searching by Learning: Exploring Artificial General Intelligence on Small Board Games by Deep Reinforcement Learning
In deep reinforcement learning, searching and learning techniques are two important components. They can be used independently and in combination to deal with different problems in AI, and have achieved impressive results in game playing and robotics. These results have inspired research into artificial…
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Exploring Images With Deep Learning for Classification, Retrieval and Synthesis
In 2018, the number of mobile phone users will reach about 4.9 billion. Assuming an average of 5 photos taken per day using the built-in cameras would result in about 9 trillion photos annually.
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Enhancing Autonomy and Efficiency in Goal-Conditioned Reinforcement Learning
Reinforcement learning is a framework that enables agents to learn in a manner similar to humans, i.e. through trial and error. Ideally, we would like to train a generalist agent capable of performing multiple tasks and achieving various goals.
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Aske PlaatFaculty of Science
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Bayesian learning: challenges, limitations and pragmatics
This dissertation is about Bayesian learning from data. How can humans and computers learn from data?
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Centre for Professional Learning
This page is currently only available in Dutch. Click here to view this page in Dutch.
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Self-directed language learning using mobile technology in higher education
This dissertation aims to explore how university students use mobile technology for their self-directed language learning and investigate factors influencing their self-directed learning with mobile technology.
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Learning Analytics and Data Science
Exploring the value of data-driven approaches in education: collecting, analysing, and interpreting data from educational environments to improve teaching and learning outcomes.
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Assessing Learning in Higher Education
Assessing Learning in Higher Education addresses what is probably the most time-consuming part of the work of staff in higher education, and something to the complexity of which many of the recent developments in higher education have added. Getting assessment ‘right’– that is, designing and implementing…
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Hybrid Quantum-Classical Metaheuristics for Automated Machine Learning Applications
This thesis investigates how quantum, quantum-inspired, and hybrid quantum-classical computation can enhance key points of the automated machine learning (AutoML) pipeline under the constraints of noisy intermediate-scale quantum (NISQ) devices.
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Effects of the early social environment on song and preference learning in zebra finches
Songbirds as vocal learners learn their songs and song preference from social tutors. Tutor choice for both song and preference learning are important to characterize for understanding individual learning performance and cultural transmission of song.
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Learn to Dare!
The ‘Leer te Durven!’ program (Learn to Dare) is a preventive training program for children with mild anxiety symptoms (Simon & Bögels, 2014). The program has been developed for children between the ages of 8 and 12 who feel or behave anxiously, avoid situations, are afraid of doing things wrong, appear…
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Reliable and Fair Machine Learning for Risk Assessment
The focus of this thesis is on the technical methods which help promote the movement towards Trustworthy AI, specifically within the Inspectorate of the Netherlands.
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Alan Kai HassenFaculty of Science
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Vision on teaching and learning
News, inspiration, background information and more about the Learning@LeidenUniversity vision on teaching and learning.