751 search results for “bender learning” in the Public website
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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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Mart MojetICLON
m.h.mojet@iclon.leidenuniv.nl | 071 5274015
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Quantum Methods for Machine Learning and Classical Dynamics
All the data stored and processed by our computers is encoded as sequences of zeros and ones, called bits. Quantum computers offer an alternative to this traditional way of encoding and manipulating information.
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Leiden Learning & Innovation Centre
LLInC supports innovative and high-quality education both within Leiden University and in partnership with academic and social organisations.
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Sietse Schröders.schroder@liacs.leidenuniv.nl | 071 5272727
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Chloe HongICLON
y.hong@iclon.leidenuniv.nl | 071 5276587
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Marit Guda
Faculty of Social and Behavioural Sciences
m.c.guda@fsw.leidenuniv.nl | 071 5276344
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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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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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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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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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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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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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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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Using Deep Learning Models in Image Processing
Deep learning has revolutionized image processing, enabling remarkable advances in fields from autonomous driving to medical diagnostics.
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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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Vision on teaching and learning
News, inspiration, background information and more about the Learning@LeidenUniversity vision on teaching and learning.
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Elise SwartFaculty of Social and Behavioural Sciences
e.k.swart@fsw.leidenuniv.nl | 071 5272727
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Suicide Prevention Skills Learning Pathway: Towards Conscious Competence
A continuous learning pathway in suicide prevention equips psychology students with essential knowledge and skills to recognise suicidality effectively and to initiate the conversation about it.
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Mario de JongeICLON
m.o.de.jonge@iclon.leidenuniv.nl | 071 5274027
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Björn van Zwolb.e.van.zwol@liacs.leidenuniv.nl | 071 5272727
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Kim Stroet
Faculty of Social and Behavioural Sciences
k.f.a.stroet@fsw.leidenuniv.nl | 071 5273955
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Deep learning for tomographic reconstruction with limited data
Tomography is a powerful technique to non-destructively determine the interior structure of an object.Usually, a series of projection images (e.g.\ X-ray images) is acquired from a range of different positions.
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Geerte Holwerda-van den BergICLON
g.h.holwerda@iclon.leidenuniv.nl | 071 5276313
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Emma EveraertFaculty of Social and Behavioural Sciences
e.everaert@fsw.leidenuniv.nl | 071 5272727
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Marga HarmantoICLON
m.d.harmanto@iclon.leidenuniv.nl | 071 5275548
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Machine Learning in Quantum Sciences
Cambridge University Press has published a new book co-authored by researchers from Leiden University, offering both an introduction to machine learning and deep neural networks, and an overview of their applications in quantum physics and chemistry — from reinforcement learning for controlling quantum…
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Learning from the past
Leiden archaeologists investigate how people in the past impacted their environment. Together with scientists, environmental scientists, and humanities experts, they use this information to draw conclusions about the present – and show what we can learn from it for the future.
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Professional learning communities in pre-vocational secondary schools: Effects of interdependency on differentiated teaching
Three types of PLCs are studied, varying on the dimension of autonomy of and interdependency between teachers: Joint work, Aid and assistance and Shared practices.
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Deep Learning Solutions for Domain-Specific Image Segmentation
Image segmentation is a fundamental task in computer vision, with applications ranging from medical diagnostics to archaeological research.
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Aske Plaata.plaat@liacs.leidenuniv.nl | 071 5277065
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progress data in planning and evaluating instruction for students with learning disabilities
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Proteochemometrics
Research question
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Professional learning communities for mentors of novice teachers
Professional learning communities are useful for professionalization but also for the development of induction programmes. In this project, we combine these two worlds into a professional learning communities in which mentors or novice teachers learn about mentoring and at the same time develop an induction…
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Statistical learning for complex data to enable precision medicine strategies
Explaining treatment response variability between and within patients can support treatment and dosing optimization, to improve treatment of individual patients.
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Learning by Doing in Journalism
Students at Leiden University College (LUC) gain an understanding of journalism ‘from the inside out’ through innovative teaching methods in the courses Multimedia Journalism, Investigative Journalism and Gender, Media and Conflict. By simulating the actual daily tasks of journalists, they are exposed…
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Frans Rodenburgf.j.rodenburg@biology.leidenuniv.nl | 071 5272727
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Learning assessment in online higher education
The main interest of this project concerns learners’ perceived learning outcomes in massive open online courses and the factors related to their perceived learning outcomes.
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Spaces and Support for Active Learning & Teaching
Within the Vision on Teaching and Learning, one of the 8 ambitions is Activating Teaching and Learning. With the support of the Vice-Deans and Vice-Rector, Hester Bijl, the Saltswat project is working on accelerating this ambition. What is the purpose of this site? Being effective…
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Machine learning-based NO2 estimation from seagoing ships using TROPOMI/S5P satellite data
The marine shipping industry is one of the strongest emitters of nitrogen oxides (NOx), a pollutant detrimental to ecology and human health. Over the last 20 years, the pollution produced by power plants, the industry sector, and cars has been decreasing.
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The crucible of war: Dutch and British military learning processes in and beyond southern Afghanistan
To what extent have the Dutch and British militaries learned from their counterinsurgency operations in southern Afghanistan between 2006 and 2020?
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Spaces for Active Teaching and Learning (SALT)
Here you will find an overview of the Spaces for Active Teaching and Learning already implemented at Leiden University and LUMC. These rooms vary in size, location, material affordances, and technological affordances, and thus vary in the forms of pedagogy they best support. You can use this site as…
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Education
The Learning and Behavior Problems in Education program group is responsible for teaching in the area of learning problems.
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Redefining our vision on teaching and learning
In a rapidly changing world it is crucial that our teaching keeps pace with the dynamics of society.
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The Active Learning Network & Saltswat Pilot Program
2 joint initiatives began in 2019 which attempt to connect the various efforts around active learning at Leiden University: the active learning network, and the Saltswat project.
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Support with Active Learning & Teaching (SWAT)
You can get various forms of support for you active learning ambitions. Have you already reflected on your teaching practice and have a clear idea of your goals? Your first point of contact should then be your ICTO Coordinator & ICLON. Do you want to join the network of others involved in the topic?…