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…

Promotor: J. N. Kok, Co-promotor: A. J. Knobbe

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…

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…

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…

Lecture Hall, Einsteinweg 57, 2333 CC, Leiden

How to come to valid risk stratification of alcohol use disorder?

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Lipsius, Cleveringaplaats 1, 2311 BD, Leiden

Plexus Student Centre, Kaiserstraat 25, 2311 GN, Leiden

University Library, Witte Singel 27, 2311 BG, Leiden

FSW building, Wassenaarseweg 52, 2333 AK, Leiden

Huygens, Niels Bohrweg 2, 2333 CA, Leiden

Kamerlingh Onnes Building, Steenschuur 25, 2311 ES, Leiden

Schouwburgstraat, Schouwburgstraat 2, 2511 VA, The Hague

Van Steenis, Einsteinweg 2, 2333 CC, Leiden

Snellius, Niels Bohrweg 1, 2333 CA, Leiden

Wijnhaven, Turfmarkt 99, 2511 DP, The Hague

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.

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.

We explored how to morphologically classify well-resolved jetted radio-loud active galactic nuclei (RLAGN) in the LOw Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) using machine learning.

This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…

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.

This PhD project investigates how literary translators and journalists react and respond to machine-translated metaphors and what the repercussions for professional practice are.

Promotores: Prof.dr. J. Zaanen & Prof.dr. K.E. Schalm

Legibility in the Age of Signs and Machines offers a compelling reflection on what the notion of legibility entails in a machinic world in which any form of cultural expression – from literary texts, films, artworks and museum exhibits to archives, laws, computer programs and algorithms – necessarily…

Anna van Buerenplein, Anna van Buerenplein 301, 2595 DG, The Hague

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.

In this work, I explore the creation of new methods that optimize simulations of the gravitational N-body problem. Specifically, I take advantage of the recent popularity of Machine Learning methods to find tools that can suit this problem.

Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…

The ongoing increase in antimicrobial resistance combined with the low discovery of novel antibiotics is a serious threat to our health care.

Machine Learning is becoming a more and more substantial technology for industry.

In this dissertation, we study partition-based models that can be used both for interpretable predictive modeling and for understanding data via interpretable patterns.

This thesis focuses on data found in the field of computational drug discovery. New insight can be obtained by applying machine learning in various ways and in a variety of domains. Two studies delved into the application of proteochemometrics (PCM), a machine learning technique that can be used to…

Humans can see the world through the eyes of other humans and imagine what they know, want, and intend. This competence is known as Theory of Mind.

This thesis addresses questions on effectively using variational quantum circuits for machine learning tasks.

This thesis focuses on enhancing predictions of central nervous system drug exposure using the LeiCNS-PK3.0, a physiologically based pharmacokinetic model.

Have you always wanted to use your own coffee mug at the university coffee machines but it was never accepted? We have good news for you!

Cláudio de Sá predicted the preferences of people using rankings. He adjusted ‘classical’ machine learning approaches, making them suitable for predicting preferences. His work can be applied in the prediction of election results. PhD defence on 16 December.

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…

Assistant Professor Vedran Dunjko and his team received a gift from Google to support their quantum research. The research focuses on whether quantum computers can provide new ways of understanding the mysteries of high-energy physics.

‘We hope our paper highlights the possibilities and benefits of including artificial intelligence in quantum physics to do new discoveries.’ Vedran Dunjko of the Leiden Institute of Advanced Computer Science contributed to a paper that was published in PNAS last year and now received a Cozzarelli Prize…

What began as a PhD project has grown into a website with 120,000 unique visitors each year. With the platform OpenML, researcher Jan van Rijn is contributing to open science, aiming to make machine learning more transparent, accessible, and fair.

Bright explosions appear all over the radio and gravitational-wave sky. This dynamic side of the universe which has just been discovered, can be mapped by self-learning machines. The National Science Agenda granted 5 million euro’s to CORTEX, the Center for Optimal, Real-Time Machine Studies of the…

It is a common technique in global optimization with expensive black-box functions to learn a surrogate-model of the response function from past evaluations and use it to decide on the location of future evaluations.