911 search results for “machine” in the Public website
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Julian Karch
Faculteit der Sociale Wetenschappen
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Mert Yazan
Science
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Fons Verbeek
Science
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Michael Lew
Science
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Ruchella Kock
Faculteit der Sociale Wetenschappen
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Jan van Rijn
Science
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Matt Young
Faculty Governance and Global Affairs
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Evaluation of Different Design Space Description Methods for Analysing Combustion Engine Operation Limits
Promotor: Prof.dr. T.H.W. Bäck
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Multi-dimensional feature and data mining
In this thesis we explore machine and deep learning approaches that address keychallenges in high dimensional problem areas and also in improving accuracy in wellknown problems. In high dimensional contexts, we have focused on computational fluid dynamics (CFD) simulations.
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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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Protein motions revealed by paramagnetic NMR spectroscopy
Hass
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Towards High Performance and Efficient Brain Computer Interface Character Speller: Convolutional Neural Network based Methods
A P300-based Brain Computer Interface character speller, also known as P300 speller, has been an important communication pathway, under extensive research, for people who lose motor ability, such as patients with Amyotrophic Lateral Sclerosis or spinal-cord injury because a P300 speller allows human-beings…
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Niki van Stein
Science
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Matthijs van Leeuwen
Science
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Tom Wilderjans
Faculteit der Sociale Wetenschappen
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Md Faysal Tareq
Science
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Evert van Nieuwenburg
Science
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Bertram de Boer
Science
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Nuno De Mesquita César de Sá
Science
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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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By Heritage Quest
Read all papers and other types of publication created by the project.
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Ada Lovelace Distinguished Lecture Series
The Ada Lovelace Distinguished Lecture Series brings outstanding computer scientists from around the world to Leiden University. The lecturers will share exciting ideas and results from the forefront of computer science.
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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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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
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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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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Algorithms combat environmental pollution from ships
Did you know that algorithms can help with the prevention of air pollution and ships sinking in the sea? A team of Leiden University researchers have worked together with the Dutch Ministry of Infrastructure and Water Management to look in data-driven inspection of ships. In this interview, Gerrit Jan…
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Data Mining and Sports
Collecting data in sports increased in importance the last few years.
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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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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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Applied Linguistics and AI Discussion Series: "Using machine translation for language learning in the classroom"
Lecture, Discussion
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chromophores - a platform for light responsive nanosystems and molecular machines
Lecture
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EPP meta-measure and rethinking machine learning benchmarks: A recipe for meta-learning success?
Lecture
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Machine Learning and Deep Learning Approaches for Multivariate Time Series Prediction and Anomaly Detection
PhD defence
- SAILS Lunch Time Seminar: Machine learning for spatio-temporal datasets + SAILS data observatory
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XAIPRE - Explainable AI For Predictive Maintenance
The project XAIPre (pronounce “Xyper”) aims to develop predictive maintenance system for the maritime industry using sensor technology and artificial intelligence. The project aims at developing Explainable Predictive Maintenance (XPdM) algorithms that do not only provide the engineers with a prediction…
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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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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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CIMPLO – Maintenance prediction for industries
Researchers of the Leiden Institute of Advanced Computer Science (LIACS) have started a 4 year project on developing a system that sends out automatic alerts when components from engines are showing first signs of fatigue.
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To explore the drug space smarter: Artificial intelligence in drug design for G protein-coupled receptors
Over several decades, a variety of computational methods for drug discovery have been proposed and applied in practice. With the accumulation of data and the development of machine learning methods, computational drug design methods have gradually shifted to a new paradigm, i.e. deep learning methods…
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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.
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MAPHSA - Mapping the Archaeological Pre-Columbian Heritage in South America
The archaeological heritage of South America is facing increasing threats due to the expansion of agricultural activities, infrastructure expansion, illegal wood harvesting, and the current fire emergency plaguing the Amazon and other biomes of the continent.
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European grant to advance self-learning capabilities of quantum computers
A major grant for research into machine learning algorithms for quantum computers. With this ERC Consolidator grant, Vedran Dunjko and his colleagues hope to discover which real-world problems a quantum computer can solve faster than a normal one.
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Multimodal Data and Machine Learning in the Study of Psychiatric Disorders
PhD defence
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Automated Machine Learning for Dynamic Energy Management using Time-Series Data
PhD defence
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sarcoma and non-sarcoma clinical data with statistical methods and machine learning techniques
PhD defence
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after anterior cervical discectomy: From inferential statistics to Machine Learning
PhD defence