Open topics for theses and practical courses

Unless otherwise specified, all topics are available as practical course (P1/P2), bachelor or master thesis.

 

Work group:
Type:

 

A Unified Perception of Density for Clustering [Master Thesis]


Internal Evaluation for Density-based Clustering


Clustering on Trajectories: Finding Dynamic Domains in Molecular Dynamics Data [Practical Course or Master Thesis]


3d-Shape Descriptors and Molecular Descriptors for Clustering [Practical Course or Master Thesis]


Permutation-aware Graph Similarities


Graph Neural Networks and Molecular Fingerprints


Permutation Invariant Neural Architectures


Explaining Graph Neural Networks


Expressivity of Graph Invariants


Gradual Weisfeiler-Leman Refinement


Building self-explanatory transparent models


Causal Structure Learning for Questionnaires


Attentive pixel prediction (Reinforcement Learning)


Machine learning based climate model weighting


The Complexity of Computing the Graph Edit Distance


Reinforcement Learning for improving mental health treatments


Information-theoretic measures and the EEG time series of depression patients [Master Thesis]


Efficient algorithms for uncertain graphs [Master Thesis]


Common Subgraph Problems in Tree-Like Graphs


Dynamic Orbit Partition [Practical Course or Master Thesis]


Interpretable and Explainable Deep Learning


Dynamic Information Acquisition in Questionnaires


Deep Probabilistic Clustering for Heterogeneous and Incomplete Data


Multi-agent Reinforcement Learning under Mismatch


Multi-agent Teaching Primitives


Abstraction in Reinforcement Learning


Bivariate causal measures: Experiments with existing causal methods in python on synthetic and real data [Practical Course]


Oracle analysis of distant supervision errors


Weakly supervised discourse relation prediction


Incomplete Schema Relation Clustering


Weakly supervised learning with latent class predictions


Gradient matching for semi-supervised learning


Threshold-finding for knowledge-base completion using Gaussian processes


Path-based knowledge-base completion


Better sentence representations based on BERT


Explainable Policies for Game Play [Master Thesis]


Learning Composable Policies [Master Thesis]


The Cost of Feedback


Reinforcement Learning for Optimizing Electronic Circuit Design [Practical Course]


2D pharmacophore descriptors for machine learning and similarity searches


Causal inference for wind turbine extreme events [Bachelor or Master thesis]


Clustering of spatio-temporal climatological data [Master thesis]


Reinforcement Learning from Implicit and Explicit Feedback


Machine Learning for Personalized Education [Practical Course or Bachelor Thesis]


Probabilistic Models of Multimodal Distributions


Reward Inference for Sequential Decision Making from Diverse and Implicit Feedback [Master Thesis]


Imitation Learning Under Domain Mismatch


Selecting Sequences of Items for Non-monotone functions [Bachelor or Master Thesis]


Posterior Consistency in Partial Variational Autoencoders


Evaluation of different nowcasting techniques and data bases for temperature nowcasting


Causal inference among climatological time series with extreme events [Master thesis]


Implementation of Data Mining Approach for Short-range Temperature Forecasts


Completed

  • Wei Chen, Bachelor Thesis: "Mining Brain Networks", winter term 2022/2023
  • Kejsi Hoxhallari, Bachelor Thesis: "Statistical validation and visualization of causal inference with extremes in wind-turbine data set", winter term 2022/2023
  • Daan Scheepens, Master Thesis: "A deep convolutional RNN model for spatio-temporal prediction of wind speed extremes in the short-to-medium range for wind energy applications", winter term 2021/2022
  • Yigit Berkay Bozkurt, Bachelor Thesis: "Anomaly Detection by Heterogenous Graphical Granger Causality and its Application to Climate Data", 2019
  • Christina Pacher, Bachelor Thesis: "Clustering Weather Stations: A Clustering Application for Meteorological Data", summer term 2019
  • Thomas Spendlhofer, Bachelor Thesis: "Evaluating the usage of Tensor Processing Units (TPUs) for unsupervised learning on the example of the k-means algorithm", summer term 2019
  • Ernst Naschenweng, Bachelor Thesis: "A cache optimized implementation of the Floyd-Warshall Algorithm", summer term 2018
  • Hermann Hinterhauser, Bachelor Thesis: "ITGC: Information-theoretic grid-based clustering", summer term 2018, accepted paper in EDBT 2019 (download available here)
  • Mahmoud A. Ibrahim, Bachelor Thesis: "Parameter Free Mixed-Type Density-Based Clustering", winter term 2017/2018, accepted paper in DEXA 2018 (download available here)
  • Markus Tschlatscher: "Space-Filling Curves for Cache Efficient LU Decomposition", winter term 2017/2018
  • Theresa Fruhwuerth, Master Thesis: "Uncovering High Resolution Mass Spectrometry Patterns through Audio Fingerprinting and Periodicity Mining Algorithms: An Exploratory Analysis", summer term 2017
  • Robert Fritze, PR1 "Combining spatial information and optimization for locating emergency medical service stations: A case study for Lower Austria", summer term 2017
  • Alexander Pfundner, PR2 "Integration of Density-based and Partitioning-based Clustering Methods", summer term 2017
  • Anton Kovác, Katerina Hlavácková-Schindler, Erasmus project, "Graphical Granger Causality for Detection Temporal Anomalies in EEG Data", winter term 2016/2017 (download available here)