Blar i Faculty of Mathematics and Natural Sciences på emneord "Machine Learning"
Viser treff 1-14 av 14
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Combining Query Rewriting and Knowledge Graph Embeddings for Complex Query Answering
(Master thesis, 2023-06-01)The field of complex query answering using Knowledge Graphs (KGs) has seen substantial advancements in recent years, primarily through the utilization of Knowledge Graph Embeddings (KGEs). However, these methodologies often ... -
Communication in Turn Based Multiplayer Games Using Deep Reinforcement Learning
(Master thesis, 2022-09-01)This work investigates communication in cooperative settings of multi-agent reinforcement learning. We look at what conditions make it easier or harder for meaningful communication to arise between the agents. This includes ... -
Detecting inosine in nanopore sequencing data with machine learning
(Master thesis, 2021-08-13)Detecting modifications in DNA has been a long-standing challenge in understanding the workings of the genome, particularly with regards to regulatory function. The currently most widely used sequencing technology, NGS, ... -
Evaluation and Improvement of Machine Learning Algorithms in Drug Discovery
(Master thesis, 2022-06-01)Drug discovery plays a critical role in today’s society for treating and preventing sickness and possibly deadly viruses. In early drug discovery development, the main challenge is to find candidate molecules to be used ... -
Machine Learning Approaches in Imaging Genetics
(Master thesis, 2021-06-01)Established approaches in imaging genetics and genome wide association studies (GWAS) such as univariate, multivariate and voxel-wise approaches, are prone to certain disadvantages such as being computationally expensive, ... -
Machine Learning based Detection and Identification of Trees using High Resolution Satellite Images
(Master thesis, 2021-06-01) -
Machine Learning in Automated Segmentation of Small Lesions in Magnetic Resonance Imaging for Multiple Sclerosis
(Master thesis, 2023-06-02) -
MetZoom: A CNN/LSTM hybrid based model for water reservoir inflow prediction
(Master thesis, 2022-06-01)Hydropower reservoir volumes fluctuate as water levels increase or decrease according to precipitation, valve output and inflow through water retained in the surrounding area. Predicting these fluctuations with machine ... -
Modelling of Brainstem Toxicity Including Variable Relative Biological Effectiveness in Paediatric Proton Therapy
(Master thesis, 2021-06-01)Brainstem necrosis is a rare but severe side-effect following paediatric proton therapy. Substructures of the brainstem may be associated with regional differences in radiosensitivity, but these are not accounted for ... -
Multi-step Ahead Inflow Forecasting for a Norwegian Hydro-Power Use-Case, Based on Spatial-Temporal Attention Mechanism
(Master thesis, 2023-06-02)Hydrological forecasting has been an ongoing area of research due to its importance to improve decision making on water resource management, flood management, and climate change mitigation. With the increasing availability ... -
Reinforcement Learning for Lifelong Multi-Agent Pathfinding in AutoStore system
(Master thesis, 2023-05-25)AutoStore (AS) uses a cubic system for warehouse automation, utilizing robots to retrieve and organize objects in a three-dimensional grid of bins in a Manhattan geometry environment. Lifelong Multi-Agent Pathfinding (LMAPF) ... -
Rule mining on extended knowledge graphs
(Master thesis, 2022-06-01) -
SmartSwarm - A Multi-Agent Reinforcement Learning based Particle Swarm Optimization Algorithm
(Master thesis, 2023-06-01)Particle Swarm Optimization is a renowned continuous optimization method that utilizes Swarm Intelligence to find solutions to complex non-linear optimization problems efficiently. Since its proposal, many developments ... -
Vessel recognition in ultrasound images using machine learning techniques
(Master thesis, 2023-06-02)Purpose: Ultrasound is an imaging modality that is commonly used during cardiovascular surgeries globally. The purpose of this thesis is to investigate how machine learning techniques can be used to identify vessel properties ...