966 search results for “machine archeologie” in the Public website
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Exploring big data approaches in the context of early stage clinical
Als gevolg van de grote technologische vooruitgang in de gezondheidszorg worden in toenemende mate gegevens verzameld tijdens de uitvoering van klinische onderzoeken.
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Machine Learning Improves Cross-border Tax Estimates
Multidisciplinary research has established that VAT-results are in practice six times lower than what it should have been. The new estimates rely on machine learning techniques.
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Network analysis methods for smart inspection in the transport domain
Transport inspectorates are looking for novel methods to identify dangerous behavior, ultimately to reduce risks associated to the movements of people and goods. We explore a data-driven approach to arrive at smart inspections of vehicles.
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Optimally weighted ensembles of surrogate models for sequential parameter optimization
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.
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MRI Machine at the Nanoscale Breaks World Records
A new NMR microscope gives researchers an improved instrument to study fundamental physical processes. It also offers new possibilities for medical science, for example to better study proteins in Alzheimer patients’ brains. Publication in Physical Review Applied.
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Algorithm selection and configuration for Noisy Intermediate Scale Quantum methods for industrial applications
Quantum hardware comes with a different computing paradigm and new ways to tackle applications. Much effort has to be put into understanding how to leverage this technology to give real-world advantages in areas of interest for industries such as combinatorial optimization or machine learning.
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Methods and Tools for Mining Multivariate Time Series
Mining time series is a machine learning subfield that focuses on a particular data structure, where variables are measured over (short or long) periods of time.
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Alumnus Robert Ietswaart: ‘Machine learning is revolutionising drug discovery’
Robert Ietswaart does research into gene regulation at the famous Harvard Medical School in Boston. He developed an algorithm to better predict whether a candidate medicine is going to produce side effects. He studied mathematics and physics in Leiden, and gained his PhD in computational biology in…
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Robust rules for prediction and description.
In this work, we attempt to answer the question:
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Spectral imaging and tomographic reconstruction methods for industrial applications
Radiography is an important technique to inspect objects, with applications in airports and hospitals. X-ray imaging is also essential in industry, for instance in food safety checks for the presence of foreign objects.
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Numerical exploration of statistical physics
In this thesis, we examine various systems through the lens of several numerical methods.
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Data-Driven Risk Assessment in Infrastructure Networks
Leiden University and the Ministry of Infrastructure and Water Management are involved in a collaboration in the form of a research project titled 'Data-Driven Risk Assessment in Infrastructure Networks'.
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A document classifier for medicinal chemistry publications trained on the ChEMBL corpus
Source: J Cheminform, Volume 6, Issue 1 (2014)
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special about human intelligence, that it cannot be replicated in a machine’
Is the possibility of computers making decisions for us in the future realistic? Holger Hoos, professor of Machine Learning, gives his opinion about the future of artificial intelligence in the television show ‘The future is fantastic’ on NPO3.
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Leiden Classics: Bibliotheca Thysiana, a 17th century time machine
From once controversial scientific works and historical bibles, to personal shopping lists and clothing bills. The 17th-century Bibliotheca Thysiana and the archive of the collector Johannes Thysius exhibit both the intellectual and everyday life as it was three hundred years ago. Now a brand-new digital…
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'The use of online translation machines in healthcare settings may involve certain risks'
Researcher and lecturer Susana Valdez investigates how migrants make use of online translation technology in medical situations. Her research suggests that they often encounter obstacles when using machine translation in these settings. Potential problems include a lack of understanding or trust.
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Correspondence article by Eduard Fosch-Villaronga in Nature Machine Intelligence
Robot technology is flourishing in multiple sectors of society, from retail, health care, industry and education. However, are robots representative towards minority groups of society, like LGBTQ+ people?
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The Use of Machine Learning in Public Organizations - an Interview with PhD Student Friso Selten
Friso Selten recently started a PhD position that is part of the SAILS program. This PhD project is a collaboration between FGGA, LIACS, and eLaw, and is supervised by Bram Klievink (FGGA), Joost Broekens (LIACS), and Francien Deschene (eLaw). In the project Friso will investigate the influence of artificial…
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Ghost in the machine: the deep features of Yanming Guo
In the 1960s at MIT, cognitive scientist Marvin Minsky told a couple of graduate students to program a computer to perform the simple task of recognising objects in pictures, thinking it would be a nice summer project. Scientists from Leiden and the rest of the world are still working on it today.
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Structured Parallel Programming for Monte Carlo Tree Search
The thesis is part of a bigger project, the HEPGAME (High Energy Physics Game). The main objective for HEPGAME is the utilization of AI solutions, particularly by using MCTS for simplification of HEP calculations.
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Tom Kouwenhoven
Science
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Julia Wasala
Science
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Surendra Balraadjsing
Science
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Unwinding a hank of yarn: how do cellular machines unfold misfolded proteins?
Protein chains typically fold to function. Folding is a complex process and if done correctly leads to a unique functional fold topology for a given protein chain. Other topologies are also possible but are often non-functional or toxic. These misfolded proteins are then unfolded and subsequently refolded…
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Data-driven donation strategies: understanding and predicting blood donor deferral
The research in this dissertation aims to optimise blood donation processes in the framework of the Dutch national blood bank Sanquin. The primary health risk for blood donors is iron deficiency, which is evaluated based on donors' hemoglobin and ferritin levels.
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The BIAS project at the Applied Machine Learning Days in Lausanne, Switzerland
The Applied Machine Learning Days AMLD is a global platform that brings together experts and participants from over 40 countries across industry, academia, and government in the field of Machine Learning. In this year’s edition, members of the BIAS project organized a track around the topic Fairness…
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Chen Li
Science
- Core members
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Correspondence article by Eduard Fosch-Villaronga in Nature Machine Intelligence
Robot technology is flourishing in multiple sectors of society, including retail, health care, industry and education. However, are robots representative towards minority groups of society, like LGBTQ+ people?
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Using cryo-EM methods to uncover structure and function of bacteriophages
Bacteriophages, or phages for short, are the most abundant biological entity in nature. They shape bacterial communities and are a major driving force in bacterial evolution.
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Noord-Brabantse Oudheden
C.R. Hermans (2012). Facsimile-editie van Noordbrabants Oudheden aangevuld met enkele Archeologische Mengelwerken.
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Data-driven Predictive Maintenance and Time-Series Applications
Predictive maintenance (PdM) is a maintenance policy that uses the past, current, and prognosticated health condition of an asset to predict when timely maintenance should occur.
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Model-assisted robust optimization for continuous black-box problems
Uncertainty and noise are frequently-encountered obstacles in real-world applications of numerical optimization. The practice of optimization that deals with uncertainties and noise is commonly referred to as robust optimization.
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Data science for tax administration
In this PhD-thesis several new and existing data science application are described that are particularly focused on applications for tax administrations.
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Putting life into Late Neolithic houses
Investigating domestic crafts and subsistence activities through experiments and material analysis
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Nurbolat Kenbayev
Science
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Gerard van Westen
Science
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Rayyan Toutounji
Faculteit der Sociale Wetenschappen
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Guilherme D'Andrea Curra
Faculteit Archeologie
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Diego Barbosa Arize Santos
Faculteit der Sociale Wetenschappen
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Data Driven Modeling & Optimization of Industrial Processes
Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.
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Vidi grant for Angus Mol: ‘Historical games are like time machines’
How do games help shape our perception of the past? Associate Professor Angus Mol receives a Vidi grant to answer this question.
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Calculated Moves: Generating Air Combat Behaviour
By training with virtual opponents known as computer generated forces (CGFs), trainee fighter pilots can build the experience necessary for air combat operations, at a fraction of the cost of training with real aircraft.
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Speak up where it will help, not just at the coffee machine
For five years, Pauline Hutten put her heart and soul into the Faculty Council of the Faculty of Governance and Global Affairs (FGGA), but a short time ago, she handed over the baton to Sanneke Kuipers, who is now Chair. We met up with them both for a joint interview about the importance of particip…
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Veerkrachtig Verleden. Een reflectie op archeologie, archeologen en musea in het Anthropoceen
Inaugural lecture
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Automated de novo metabolite identification with mass spectrometry and cheminformatics
Promotor: Prof.dr. T. Hankemeier, Co-Promotores: T. Reijmers, L. Coulier
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Filter-based reconstruction methods for tomography
Promotor: K.J. Batenburg
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Novel analytical approaches to characterize particles in biopharmaceuticals
Particles are omnipresent in biopharmaceutical products. In protein-based therapeutics such particles are generally associated with impurities, either derived from the drug product itself (e.g. protein aggregates), or from extrinsic contaminations (e.g. cellulose fibers).
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High-contrast spectroscopy of exoplanet atmospheres
More than 5,000 exoplanets have been found over the past couple of decades. These exoplanets show a tremendous diversity, ranging from scorching hot Jupiters, common super-Earths, to widely separated super-Jupiters on the planet/brown dwarf boundary.
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Proteins in harmony: Tuning selectivity in early drug discovery
This thesis describes the importance of being able to control the selectivity of potential drug candidates.