340 zoekresultaten voor “machine” in de Publieke website
-
Machine Learning
Computers zijn in staat om ongelooflijk nauwkeurige voorspellingen te doen op basis van machine learning. Met andere woorden, deze computers kunnen zonder tussenkomst leren als ze eenmaal door mensen zijn voorgeprogrammeerd. Bij LIACS verkennen en verleggen we de grenzen van wat een revolutionaire nieuwe…
-
Massively collaborative machine learning
Promotor: J. N. Kok, Co-promotor: A. J. Knobbe
-
Kunstgebitten, machines en stof
Over onorthodoxe uitingen van wetenschap.
-
Kunstmatige intelligentie en machine learning
Computers zijn in staat om ongelooflijk nauwkeurige voorspellingen te doen op basis van machine learning. Met andere woorden, deze computers kunnen zonder tussenkomst leren als ze eenmaal door mensen zijn voorgeprogrammeerd. Bij LIACS verkennen en verleggen we de grenzen van wat een revolutionaire nieuwe…
-
Machine learning for radio galaxy morphology analysis
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.
-
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.
-
Computational speedups and learning separations in quantum 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…
-
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.
-
Mens in de machine (najaar 2022)
Eerlijke en creatieve AI
-
The holographic glass bead game: from superconductivity to time machines
Promotores: Prof.dr. J. Zaanen, Prof.dr. K.E. Schalm
-
Postdoc on Causal Machine Learning for Spatio-temporal Datasets
Wiskunde en Natuurwetenschappen, Leiden Institute of Advanced Computer Science (LIACS)
-
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.
-
Automated machine learning for dynamic energy management using time-series data
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…
-
space of post-translationally modified peptides in Streptomyces with machine learning
The ongoing increase in antimicrobial resistance combined with the low discovery of novel antibiotics is a serious threat to our health care.
-
Data-Driven Machine Learning and Optimization Pipelines for Real- World Applications
Machine Learning is becoming a more and more substantial technology for industry.
-
Quantum machine learning: on the design, trainability and noise-robustness of near-term algorithms
This thesis addresses questions on effectively using variational quantum circuits for machine learning tasks.
-
2 Lecturer positions (0.6-1.0 FTE) in Computer Science, Machine Learning, and AI
Wiskunde en Natuurwetenschappen, Leiden Institute of Advanced Computer Science (LIACS)
-
PhD candidate, Feature-based machine learning for precision diagnosis of neuromuscular diseases
Wiskunde en Natuurwetenschappen, Leiden Institute of Advanced Computer Science (LIACS)
-
The flux and flow of data: connecting large datasets with machine learning in a drug discovery envirionment
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…
-
The Little Green Machine
Onderzoekers uit de informatica, wiskunde, meteorologie, materiaalbouw natuur- en sterrenkunde hebben gezamenlijk een oplossing gevonden voor hun grote behoefte aan rekenvermogen. De diverse groep onderzoekers heeft voor de bouw van een revolutionaire supercomputer, die
-
Machine learning voorspelt voorkeuren
Cláudio de Sá voorspelt voorkeuren van mensen door gebruik te maken van ranglijsten. Dit doet hij door ‘klassieke’ machine learning-technieken aan te passen. Zijn werk kan onder andere gebruikt worden om de uitslagen van verkiezingen te voorspellen. Promotie op 16 december.
-
PNAS Paperprijs voor quantum machine learning
‘We hopen dat ons artikel de mogelijkheden en voordelen laat zien van het gebruik van kunstmatige intelligentie in de quantumfysica om nieuwe ontdekkingen te doen.’ Vedran Dunjko van het Leiden Institute of Advanced Computer Science droeg bij aan een artikel dat vorig jaar verscheen in PNAS. Het artikel…
-
Novel system-inspired model-based quantum machine learning algorithm for prediction and generation of High-Energy Physics data
De huidige en toekomstige quantumcomputers vormen dezelfde uitdaging als de laser in zijn begindagen. In theorie werd voorspeld dat de laser een bron van zeer speciaal, zeer krachtig licht zou zijn. Maar in die tijd waren er geen duidelijke toepassingen voor. Critici van het idee noemden het een probleem…
-
Geest in de machine: de diepe kenmerken van Yanming Guo
In de jaren zestig droeg cognitiewetenschapper Marvin Minsky aan MIT enkele van zijn studenten op een computer te programmeren om een eenvoudige taak uit te voeren: objectherkenning in foto's. Hij dacht dat het een aardig zomerproject zou zijn. Wetenschappers uit Leiden en de rest van de wereld werken…
-
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.
-
Modelling the interactions of advanced micro- and nanoparticles with novel entities
Novel entities may pose risks to humans and the environment. The small particle size and relatively large surface area of micro- and nanoparticles (MNPs) make them capable of adsorbing other novel entities, leading to the formation of aggregated contamination.
-
Alumnus Robert Ietswaart: 'Machine learning leidt tot een revolutie in de medicijnontwikkeling'
Robert Ietswaart doet bij de befaamde Harvard Medical School in Boston onderzoek naar humane genregulatie. Hij ontwikkelde een machine learning-algoritme om beter te kunnen voorspellen of een kandidaatmedicijn bijwerkingen kan gaan vertonen. Ietswaart studeerde wiskunde en natuurkunde in Leiden, en…
-
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.
-
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.
-
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.
-
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.
-
Numerical exploration of statistical physics
In this thesis, we examine various systems through the lens of several numerical methods.
-
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'
-
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.
-
Robust rules for prediction and description.
In this work, we attempt to answer the question:
-
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.
-
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.
-
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.
-
Frans Rodenburg
Wiskunde en Natuurwetenschappen
f.j.rodenburg@biology.leidenuniv.nl | +31 71 527 2727
-
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.
-
Chen Li
Wiskunde en Natuurwetenschappen
c.li@cml.leidenuniv.nl | +31 71 527 2727
-
Wouter van Loon
Faculteit der Sociale Wetenschappen
w.s.van.loon@fsw.leidenuniv.nl | +31 71 527 2727
-
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.
-
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.
-
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.
-
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.
-
Sociaal ingebedde AI-systemen
Dit interdisciplinair onderzoeksproject verkent verschillende adaptieve machine-learning methoden die inzicht kunnen geven in de interactie tussen mens en machine. Het uiteindelijke doel is een open en natuurlijke communicatie tussen mens en AI die moet resulteren in wederzijds vertrouwen, samenwerking…
-
Applied Machine Learning in Neurosurgical Oncology
Promotie
-
Onze faciliteiten
Ter ondersteuning van het onderzoek en onderwijs beschikt het Leiden Institute of Advanced Computer Science (LIACS) over een apart Onderzoek & Onderwijs Laboratorium. Binnen deze omgeving kunnen wij apparatuur bieden die verder gaat dan normale kantoorautomatisering en productie.
-
Filter-based reconstruction methods for tomography
Promotor: K.J. Batenburg