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Protein Structure and Sequence Co-Design through Graph Based Generative Diffusion Modeling

Bhuradia, Mehul (author)

Proteins are fundamental biological macromolecules essential for cellular structure, enzymatic catalysis, and immune defense, making the generation of novel proteins crucial for advancements in medicine, biotechnology, and material sciences. This study explores protein design using deep generative models, specifically Denoising Diffusion...

master thesis 2024

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General Tree Evaluation for AlphaZero

Jaldevik, Albin (author)

Over the last decade, there have been significant advances in model-based deep reinforcement learning. One of the most successful such algorithms is AlphaZero which combines Monte Carlo Tree Search with deep learning. AlphaZero and its successors commonly describe a unified framework for tree construction and acting. For instance, build the tree...

master thesis 2024

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Detecting Long-term Behavioral Adaptations in Assisted Driving: An Automated Approach Using Neural Networks and Novelty Detection

Oude Elferink, Rens (author)

The autonomous vehicle industry has the potential to revolutionize the future of driving, making the understanding of vehicle-driver interactions crucial as we progress towards fully autonomous systems. Advanced Driver Assistance Systems (ADAS) are integral in this evolution, bridging the gap between automated and manual driving. Research...

master thesis 2024

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Semi-Supervised Integrated Learning of Mutational Signatures for Predicting DNA Repair Pathway Deficiencies

Tofacchi, Tommaso (author)

<b>Motivation</b>. DNA molecules mutate thousands of times every day. Some mutations are harmful to human cells, and may lead to the loss of function in important genes involved in DNA damage repair (DDR) mechanisms. Diseases such as tumors can exploit mutations in important, driver DDR genes to rapidly proliferate. Specific patterns of...

master thesis 2024

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A comparative study of Theory of Mind mechanisms and tasks between human and AI

van Rhenen, Jan-Willem (author)

In order to develop artificial agents that can understand social interactions at a near-human level, it is required that these agents develop an artificial Theory of Mind; the ability to infer the mental state of others. However, developing this artificial Theory of Mind is a highly difficult process. This is because Theory of Mind is an...

master thesis 2023

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Using Social Signal Processing and Conversational Agent To Aid People in their Negotiation Skills: Self-awareness through Mimicry

Chen, Weilun (author)

Negotiation is not a skill that comes naturally to most people. However, most people could benefit from attaining good negotiation skills. Non-verbal behaviour plays an important role in negotiations. Previous studies have shown a link between mimicry through conversational agents and self-regulation of non-verbal behaviour. The current study...

master thesis 2023

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Constraint Handling in RV-GOMEA

Koch, Johannes (author)

The Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm (RV-GOMEA) is a state-of-the-art algorithm for single-objective, real-valued optimization. As many practical applications are inherently constrained, evolutionary algorithms are equipped with constraint handling techniques to allow optimizing constrained problems. The approach...

master thesis 2023

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Elastic gradient boosting decision trees under limited labels by sequential epistemic uncertainty quantification: Elastic CatBoost Uncertainty (eCBU)

Sennema, Erik (author)

Intrusion detection systems (IDSs) are essential for protecting computer systems and networks from malicious attacks. However, IDSs face challenges in dealing with dynamic and imbalanced data, as well as limited label availability. In this thesis, we propose a novel elastic gradient boosting decision tree algorithm, namely Elastic CatBoost...

master thesis 2023

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Maxplain – Value-based Evaluation of Explainable AI Techniques

Deb, Sreeparna (author)

A 2022 Harvard Business Review report critically examines the readiness of AI for real-world decision-making. The report cited several incidents, like an experimental healthcare chatbot suggesting a mock patient commit suicide in response to their distress or when a self-driving car experiment was called off after it resulted in the death of a...

master thesis 2023

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MAPL: Model Agnostic Peer-to-Peer Learning

Mukherjee, Sayak (author)

Current methods in Federated and Decentralized learning presume that all clients share the same model architecture, assuming model homogeneity. However, in practice, this assumption may not always hold due to hardware differences. While prior research has addressed model heterogeneity in Federated Learning, it remains unexplored in fully...

master thesis 2023

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Clearing the Air: An Exploration of Pulmonologists' Needs and Intents in XAI Solutions for Respiratory Medicine

Oltmans, Rembrandt (author)

Despite the low adoption rates of artificial intelligence (AI) in respiratory medicine, its potential to improve patient outcomes is substantial. To facilitate the integration of AI systems into the clinical setting, it is essential to prioritise the development of explainable AI (XAI) solutions that improve the understanding of the AI...

master thesis 2023

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A System for Model Diagnosis centered around Human Computation

Ziad Ahmad Saad Soliman Nawar, Ziad (author)

Machine learning (ML) systems for computer vision applications are widely deployed in decision-making contexts, including high-stakes domains such as autonomous driving and medical diagnosis. While largely accelerating the decision-making process, those systems have been found to suffer from a severe issue of reliability, i.e., they can easily...

master thesis 2023

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Architectural Innovations for Efficient Denoising and Classification: A Manual vs. Neural Architecture Search Comparison

Markhorst, Thomas (author)

In this paper, we combine image denoising and classification, aiming to enhance human perception of noisy images captured by edge devices, like security cameras. Since edge devices have little computational power, we also optimize for efficiency by proposing a novel architecture that integrates the two tasks. Additionally, we alter a Neural...

master thesis 2023

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The impact of reactionary behavior in channel creation games: How actions influence transaction routing in the bitcoin lightning network

Moonen, Djoshua (author)

Payment channels allow parties to utilize the blockchain to send transactions for a cheaper fee. Previous work has analyzed to which degree a party can profit by facilitating the transaction process. The aim is to increase the usability of the network and to be rewarded for providing this service. However, previous work focuses on maximizing the...

master thesis 2023

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High-frequency Characterization and Modeling of CMOS Transistors at Cryogenic Temperature: An Artificial Neural Network Based Approach

Dutta, Deb (author)

To fulfill the vision of scalable quantum computers, cryogenic CMOS is a promising technology to implement the electronic interface for large-scale quantum processors. Research over the years has shown performance improvements in CMOS transistors in commercially viable technology at cryogenic temperatures. While the physics behind the operation...

master thesis 2023

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Inferring Robust Plans with a Rail Network Simulator

Gardos Reid, Reuben (author)

Over 700 trains in the Netherlands are used daily for passenger transportation. Train operations involve tasks like parking, recombination, cleaning, and maintenance, which take place in shunting yards. The train unit shunting problem (TUSP) is a complex planning problem made more difficult by uncertainties such as delays. Most existing...

master thesis 2023

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Machine Learning and Causal Inference for the estimation of the effect of tacrolimus on kidney rejections

Borges Carioca Moreno Rodrigues, Inês (author)

Tacrolimus is an immunosuppressive drug given to kidney transplant patients. A low concentration of this drug can lead to kidney rejection, but to our knowledge no research has been done to causally connect the two. This paper investigates the causal effect of tacrolimus concentration on kidney rejection occurrence using predictive analysis and...

master thesis 2023

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VoBERT: Unstable Log Sequence Anomaly Detection: Introducing Vocabulary-Free BERT

Hofman, Daan (author)

With the ever-increasing digitalisation of society and the explosion of internet-enabled devices with the Internet of Things (IoT), keeping services and devices secure is becoming more important. Logs play a critical role in sustaining system reliability. Manual analysis of logs has become increasingly difficult, accelerating the development of...

master thesis 2023

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DNN-porting for maximizing inference hardware utilisation at the Edge

Buijnsters, Jan (author)

Industry 4.0 and the Industrial Internet of Things (IIoT) growth will result in an explosion of data generated by connected devices. Adapting 5G and 6G technology could be the leading enabler of the broad possibilities of connecting IIoT devices in masses. However, the edge solution has some disadvantages, such as the loss of resource elasticity...

master thesis 2023

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Using metagenomic Hi-C data to discover broad host-range plasmids conferring antimicrobial resistance

Dorrestijn, Eljo (author)

Horizontal gene transfer (HGT) trough plasmids is one of the main contributors to the rapid increase of antimicrobial resistance (AMR). Studying wastewater from wastewater treatment plants (WWTPs) allows us new insights into HGT as bacteria from different sources come together. Currently the analysis of HGT is limited, as plasmids cannot be...

master thesis 2023