Advised Theses
(If not noted otherwise, supervision is by Ute Schmid)
Present
Jeremy Schierling: tba (BA AI)
Melissa Biedermann: Combining RGM Image Data with LiDAR Data for Tree Vitality Assessment (BA AI, Johannes Langer)
Christoph St??el: Ein interaktiver Tutor zur Vermittlung vo KI-Kompetenzen für KMUs (MA AI, in Kooperation mit KMU-KI-EZ)
Kemal Tanirak: Vermittlung von deklarativem Wissen durch dialogbasierte Systeme in Serious Game; Die Entwicklung eines 2D-Lernspiels auf Basis eines LLM-Modells (MA CitH)
Sonja Ruschhaupt: An Intelligent Tutoring System for Primary-level Tree Identification by Alignment and Socratic Dialogue(MA AI)
Tim B?ckel: Anomaly Detection for Thermal Images (MA AI, in coop. with Fraunhofer ISC, Judith Knoblach und Ute Schmid)
Eva Jansohn: tba (MA CitH)
Amir Moghaddam: Optimising Model Revision through Density Parameter Estimation via Augmented Near Misses and Near Hits for MNIST (MA ISoSyc, Judith Knoblach und Ute Schmid)
Mohammadkazem Vahedi: Machine Learning to Calculate Air-void in X-ray images (MA AI, mit Brose, Judith Knoblach und Ute Schmid)
Yuliia Kaidashova: tba (BA AI)
Uta G?rtner: Measuring the Effects of Logical Constraints on Explanation Quality in Proof-based Dialogues for Model Exploration (MA CitH, Bettina Finzel)
Mai Anh Vu: Integrating Large Language Models into Intelligent Tutoring Systems for Basic Arithmetic to Generate Text Exercises and Tailored Feedback (MA CitH, mit AraCom IT Services GmbH)
Normix Hillemann: Automatisierte Themenerkennung in Patienten-Chatbot-Interaktionen (MA CitH, mit Thieme Compliance)
Lukas Gernlein: Explainable interactive maschine learning for tabular data (MA AI, in cooperation with Fraunhofer IIS/CAI, Emanuel Slany)
Philippe Crackau: Examining Image Classifier Decisions Through the Lense of Probabilistic Relational Explanations – Extending the CoReX Framework by Probabilistic Logic Programming (MA CitH, Bettina Finzel)
Past
238. Jonas Schmidt: Comparing Different Fine-Tuning Strategies in Vision Transformer Training for Robust Classification of Facial Expressions (BA WI, Bettina Finzel, November 2024)
237. Leonhard Kestel: Tree Vitality Classification from Image Data - A Comparison of Multipectral Index Scores and Deep Learning Approaches (MA CitH, Projekt BaKIM, Jonas Troles, September 2024)
236. Satyam Pant: Model revision for industrial image data based on near-miss explanation guided augmentation (MA AI, in cooperation with KMU-KI-EZ, Judith Knoblach und Ute Schmid, September 2024)
235. Johannes Langer:A Neuro-symbolic Single-path Approach for Solving Raven's Progressive Matrices (MA CitH)
234.Barbara Blank: Umsetzung von NLP-Methoden für ein Intelligentes Tutorsystem zur Konzeptvermittlung mittels sokratischem Dialog – Erschlie?ung des Themenfelds heimische B?ume für die Grundschule (MA CitH)
233. Christian Dormagen: Inductive Learning of System-level Process Behaviour Explanations - A Hybrid Machine Learning Approach for Process Mining (MA AI, KIGA project, Stephan Scheele)
232. Maren Stümke: Identifying and Overcoming Student’s Misconceptions in Chemistry: An Intelligent Tutoring System to Teach Chemical Equations with Worked-out Analogical Examples (MA CitH, in cooperation with IPN Kiel, Finzel & Schmid)
231. Daniel Gramelt: Explanatory interactive machine learning for welding seam quality assessment (MA AI, in cooperation with Porsche digital, Februar 2024)
230. Jan Adelhardt: Analyzing Model-agnostic Fairness Metrics for Emotion Recognition Models (BA AI, Pahl & Schmid, in coop. with Fraunhofer IIS, December 2023)
229. Adrian V?lker: Integrating Overlays and Rules to Monitor Acquisition of Declarative and Procedural Knowledge within an Intelligent Tutor System for SQL (MA WI, December 2023)
228. Shamim Miroliaei: Exploring Potential Biases in Sequential Data Classification for Hand Gesture Recognition using Layer-wise Relevance Propagation and Cluster Analysis (MA ISoSyc, DFG PainfaceReader, Bettina Finzel, December 2023)
Die Arbeit wurde 2024 mit dem PUSh-Preis der Universit?t Bamberg ausgezeichnet.
227. Luisa Schneider: The Effects of Similarity in Example Images on Generating Interpretable Pertinent Negatives with CEM (BA AI, Finzel & Schmid, December 2023)
226. Martin Schmei?er: Evaluating methods for transcompiling high-level programming languages (MA AI, in cooperation with Siemens, November 2023)
225. Jonas Amling: Explainable AI for Mixed Data Clustering (MA AI, Fraunhofer IIS/CAI, Stephan Scheele, November 2023)
224. Sonia Simons:Comparative Analysis of U-Net and DeepLabV3+ for Tree Species Classification through Semantic Segmentation of RGB-UAV Imagery (BA Informatik, TU Berlin, Jonas Troles, BaKIM, Oktober 2023)
223. Ferdinand Lang: Effective bloat-free Genetic Programming by Means of neat-GP and Automatically Defined Functions (BA AI, September 2023)
222. Maximilian Bauer: Lernen von rekursiven Funktionen aus Beispielen: Ein Vergleich von Induktiver Funktionaler mit Induktiver Logischer Programmierung?(Learning Recursive Functions from Examples: Comparing Inductive Functional and Inductive Logic Programming, BA AI, September 2023)
221. Philipp Kastrup: Explanatory interactive machine learning: Empirical evidence for positive effects on joint performance and trust (Arbeitstitel, MA 球探足球比分, September 2023)
220. Julian Holger Fehr:Explainable Link Prediction in Knowledge Graphs with Text Literals - Enhancing the MINERVA Algorithm with SBERT (MA CitH, Wehner & Schmid, September 2023)
219. Solveig Rabsahl:Exploring the Impact of Scale of Measurement on Counterfactual Explanations (BA AI, in Koop. mit Fraunhofer IIS/HIX, Slany & Scheele, September 2023)
218. Felix Hempel:Explanatory and Interactive Machine Learning with Counterfactual Explanations for Ordinal Data (MA AI, in Koop. mit Fraunhofer IIS/HIX, Slany & Scheele, September 2023)
217. Richard Nieding:Unsupervised Machine Learning via Feature Extraction and Clustering to Classify Tree Species from High-Resolution UAV-based RGB Image Data (MA CitH, BaKIM, Troles & Schmid, August 2023)
216. Alexander Hatzold: Semantic and Syntactic Analogical Reasoning in Large Language Models (LLMs): Effects of Different Types of
Prompting on the Performance of ChatGPT (MA AI August 2023, MA AI)
215. Oraz Serdarov: Explainable Unsupervised Learning for Fraud Detection (August 2023, MA AI, cooperation with HUK-Coburg, Emanuel Slany and Ute Schmid)
214. Sonja Niemann: An Intelligent Tutor System for Recursive Programming – Identifying Different Misconceptions for Helpful Feedback (Juli 2023, MA CitH)
213. Josef Brücklmair: Explainable Text Retrieval -- Assessing Neural Rankers for Text Similarity Through Explanations (MA AI, cooperation with Datev, Ute Schmid and Sebastian Kiefer, Mai 2023)
212. Sven Nekula: Applying Bayesian Structural Time Series to Food Demand Forecasting (MA Survey Statistics, Seitz & Schmid, M?rz 2023)
211. Joshua Simon: Time Series Change Point Detection - Adaptive LSTM-Autoencoders In Comparison To Related State-Of-The-Art Algorithms (MA Survey Statistics, Seitz & Schmid, M?rz 2023)
210. Mareike Müller: Dynamic Fingerspelling Recognition Using Sequential Deep Learning (Arbeitstitel, MA AI, Johannes Rabold und Ute Schmid, Februar 2023)
209. Bianca Zimmer: Explaining Decision Boundaries of CNNs Through Prototypes, Near Hits and Near Misses - A Comparison on Multiclass Medical Image Data Utilizing LRP Heatmaps (MA Survey Statistics, TraMeExCo/PainFaceReader, Finzel & Schmid, Februar 2023)
208. Jasmin Fritz: Prototypical and near-miss explanations for intelligent tutor systems in complex visual domains -- Learning to discriminate plants (MA AI, November 2022)
207. Thomas Sedlmeir:Erkennung und Beschreibung von Manipulationen in Dokumenten (MA AI, cooperation with ic-solution GmbH, Emanuel Slany and Ute Schmid, Nobember 2022)
206. Camila Maslaton: Plant Detection and Localization Using Semantic Instance Segmentation (MA CitH, in coop. with IIS/EZRT, Oliver Scholz, November 2022)
205. Patrick Hilme: Verbally Explaining Image Classifications from Relevant Visual Features - Towards Learning Symbolic Structures Using Layer-wise Relevance Propagation and Logic Programming (MA AI, TraMeExCo, Finzel & Schmid, November 2022)
204. Bartu Soyk?k: End to end testing pipeline for Explainable AI models (MA ISoSySc, Christoph Wehner, November 2022)
203. Rebecca von der Grün: Algorithmic Debugging and analogous examples for intelligent tutoring -- An Application to English Grammer Learning (MA CitH, Oktober 2022)
202. Alisa Münsterberg: An Intelligent Tutor System for Computational Thinking -- Identifying Systematic Deviations when Executing Sorting Algortihms (BA AI, October 2022)
201. Louisa Heidrich: Combining Explanatory Interactive Learning and Fair Machine Learning – Interacting with Explanations to Uncover and Reduce Human and Machine Biases (MA CitH, September 2022)
200. Deepika Arneja: Landmark-based Classification of Facial Expressions with a Spatio-Temporal Attention Graph Neural Network (MA SoSySc, TraMeExCo/PainFaceReader, Bettina Finzel, September 2022)
199. Christian Dormagen: Exploiting Complex Relations in Process Discovery -- Applying the Inductive Logic Programming System Aleph (BA WI, Stephan Scheele and Ute Schmid, August 2022)
198. Linda Müller: Geometric Shape Detection in Sheet-Of-Light Generated 3D Data (MA CitH, with Fraunhofer IIS/EZRT Oliver Scholz, July 2022)
197. Laura Ohff: Quantum Reinforcement Learning: Learning Rare Dynamics with Quantum Circuits (BA WI, in coop. with Porsche, Ines Rieger, July 2022)
196. Simon Kuhn: Strategies for Privacy-preserving Classification of Facial Expressions (MA AI, TraMeExCo/PainFaceReader, Finzel & Schmid, July 2022)
195. Felix Schweinfest: Comparing the Performance of Memory Augmented Neural Networks in Reinforcement Learning (MA AI, Sarem Seitz, July 2022)
194. Maximilian Kukla: Unaligned image-to-image translation for 2D/3D registration (MA AI, with Siemens Healthineers, June 2022)
193. Aliya Hammad: Hierachical machine learning for balancing power consumption and predictive accuracy (Arbeitstitel, MA AI, Stephan Scheele und Julio Wi?ing, Fraunhofer IIS, May 2022)
192. Mareike Hoffmann: Erkl?rendes interaktives maschinelles Lernen in der Textklassifikation – Ein modell-agnostischer Ansatz zur semantischen Korrektur (MA CitH, with Datev, Sebastian Kiefer, May 2022)
191. Shireen Iqbal: Identifying Ground Truth in Expert Labeled Customer Order Behavior (COB) Data Using a Web Application (MA ISSS, with Infinion, May 2022)
190. Jeremias Kuhnke: Faire Klassifikatoren durch Re-Weighting versus Re-Sampling -- Ein systematischer Vergleich (BA AI, April 2022)
189. Nina Krob: Eine Multimodale Interaktive Schnittstelle zur Erkl?rung der Klassifikation Hierarchischer und Mehrwertiger Konzepte Basierend auf Logischer Programmierung (MA AI, TraMeExCo/PainFaceReader, Finzel & Schmid, March 2022)
188. Tim B?ckel: Vergleich von herk?mmlichen Texturanalysemethoden mit Methoden des maschinellen Lernens zur lokalisierten Anomalieerkennung (BA AI, with ONTEC, March 2022)
187. Shashidhar Reddy Nimmagari: Topic Classification for Intelligent Support for Requirement Specifications (MA ISSS, with Brose, March 2022)
186. Angelina Wilczewski: Axiom pinpointing for explanatory dialogs (BA WI, Stephan Scheele and Ute Schmid, February 2022)
185. Yannik Ott: An explanatory interactive machine learning approach for image classification in medical engineering (BA Medical Engineering at TH Nuremberg, Emanuel Slany and Ute Schmid, February 2022)
184. Lennart Thamm: Explaining DNNs using ILP with knowledge derived from Deep Taylor Heatmaps?(MA CitH, Rabold & Schmid, January 2022)
183. Gülsah Bauer: Effect of Hyperparameter Optimization on the Semantic Segmentation of Crops (MA CitH, with Fraunhofer IIS/EZRT Oliver Scholz, December 2021)
Die Arbeit wurde 2022 mit dem PUSh-Preis der Universit?t Bamberg ausgezeichnet.
182. Paresh Govindwar: Investigating Data Analytics Approaches for Quality Enhancement in Automotive Component Production (MA ISSS, in cooperation with BMW, Fraunhofer IIS/EKI, Scheele & Schmid, Dez. 2021)
181. Franziska Paukner: Ein intelligentes Tutor-System zum unterstützten Einstieg in die Datenbanksprache SQL (BA WI, November 2021)
180. Aline Leuner: Evaluating Mining Approaches for Categorizing Free Text in Warranty Cases (MA WI, in cooperation with Siemens Valeo, November, 2021)
179. Jan Martin: Applying Structural Analogy to Solve Abstract Reasoning Problems in a More Human-like Way (MA AI, November 2021)
178. avid Jacob: Predicting system idle times of medical imaging systems using log file data (MA AI in cooperation with Siemens Healthineers, November 2021)
177. David Hartmann: Assessing uncertainty for CNN classification -- A case study with histopathology data (MA CitH, in cooperation with Fraunhofer IIS, TraMeExCo, November 2021)
176. Sonja Ruschhaupt: Explaining Image Classifications with Near Misses and Prototypes -- An Application to Facial Expression Analysis (BA AI, TraMeExCo/PainFaceReader, Finzel & Schmid, November 2021)
175. Christoph Wehner: Applying Attribution Methods on a Long Short-Term Memory to Create Interpretable Predictions of Lane-Changing Behaviour (MA CitH, with IBM Watson Center Munich, October 2021)
174. Shweta Suresh Shetty: Irregularity detection in industrial part processing -- A comparison of instance-based and rule-based machine learning approaches (MA ISSS, in cooperation with BMW, Schmid, October 2021)
173. Antonia H?fer: Enhancing the Interactive Machine Learning Companion LearnWithME with Global Constraints for Explanation-based Model Correction (BA AI, Finzel & Schmid, Oktober 2021)
172. Syed Mamoon Ahmed: Techniques for Candidate Selection in the Context of Interactive Machine Learning to Identify Irrelevant Digital Objects -- Realizing a Prototype in Windows Environment (MA ISSS, in collaboration with Brose, September 2021)
171. Maximilian Muschalik: Beyond Contrastive Explanations for Deep Learning Models in Physical Relational Domains (MA WI, Johannes Rabold, September 2021)
170. Bj?rn Sauter: Comparing state of the art machine learning algorithms on time series data (MA WI, in coop. with Fraunhofer IIS/SCS, NIcolas Witt, August 2021)
169. Ploy Valerie Schneider: Counterfactuals as an Approach to Test Fairness in Machine Learning -- And Why Fairness in Machine Learning Affects Everyone (MA CitH, June 2021)
168. Lisa Lengenfelder: Are relations relevant in CNNs - A study based on a facial dataset (BA AI, Rabold & Schmid, April 2021)
167. Namrata Jain: Deep Transfer Learning for Time Series Regression in Chemical Production (MA ISSS, in cooperation with Wacker AG, Finzel & Schmid, February 2021)
166. Jens von der Heide: Exploring the Impact of Class Distributions on Concept Embeddings Generated with Net2Vec (MA WI, Rabold & Schmid, Januar 2021)
165. Dominik Grimme: Comparison of text mining algorithms to select sales opportunities from public procurement notices - Towards an automatic selection toolbox (MA WI, in collaboration with Siemens Advanta (IoT), Schmid & Rabold, Januar 2021)
164. Rene Kollmann: Explaining Facial Expressions with Temporal Prototypes (MA AI, Finzel & Schmid, TraMeExCo, Dezember 2020)
163. Anna Thaler: Effects of Explanations and Incorrect System Behavior on Trust in AI Systems – An Experiment for the Classification of Spatial Configurations in Archeology (BA Psy, Schmid & Rabold, Dezember 2020)
162. Regina Siegers: Vector(s) and the search for happiness: A comparison of constraint-based causal discovery methods on time-series data from multiple contexts with latent variables (MA Survey Statistics, November 2020)
161. Lynn Mosesku: The Influence of Explanations on Trust and Perceptions of Conformity -- A VR Study in Autonomous Driving (BA Psy in coop. mit HS Coburg, November 2020)
160. Michael Fuchs: Towards Fast Interactive Learning with Aleph (BA AI, Finzel & Schmid, November 2020)
159. Andreas Gilson: Segmentation Learning for 3D Plan Models (MA AI, in coop. with Fraunhofer EZRT, Oliver Scholz, November 2020)
158. Robert Wenzel: Automatic Model Selection for Time Series Data (BA WI, in coop, with COSMO Consult Münster, Schmid, Oktober 2020)
157. Jonas Troles: Gender bias in machine translation (MA CitH, Oktober 2020)
156. Jopaul John: Extraction of Information from Images using Autoencoders (MA ISSS, Rabold, September 2020)
155. Louisa Pabst: Conversion of AI Workflow from Convolutional Neural Network to Spiking Neural Network: Network Architecture, Training Process and Accuracy (MA AI, in coop.with BMW group, South Carolina, Schmid & Rabold, August 2020)
154. Christopher Otto: Comparing the Performance of Deepfake Detection Methods on Benchmark Datasets (MA WI, Rabold und Schmid, August 2020)
153. Isabel Saffer: Generierung und Evaluation von kontrastiven Erkl?rungen für die paarweise Klassifikation von Partiell Geordneten Tumorklassen in der Histopathologie (BA AI, Finzel & Schmid, TraMeExCo, August 2020)
152. Thilipkumar Sivakumaran: Predictive Maintenance: Comparison of Machine Learning methods on medical imaging systems using log file data to forecast X-Ray tubes system failures (MA Survey Statistik in coop. with Siemens Healthineers, Tobias Hipp, August 2020)
151. Ronja Pfeiffer: On the way to a green factory: Investigation of energy consumption data for energy efficient optimization (MA CitH, in coop. with BSH Hausger?te Gmbh München, August 2020)
150. Ilona Buric: Exploring the Contrastive Expalantions Method CEM for Fashion MNist (MA AI, Rabold & Schmid, August 2020)
149. Beatrix Augustin: State-of-Charge Estimation Including Uncertainty Analysis -- Combining the Information from Charging Profiles and Voltage Relaxation During Pauses Using Neutral Networks (MA Survey Statistics, in coop with Fraunhofer Institut für Verkehr und Infrastruktur IVI, July 2020)
148. Andre Hartmann: Explainable Reinforcement Learning for User-adaptive In-car Infotainment Systems (MA AI, in coop. with Porsche, Schmid & Rabold, July 2020)
147. Patrick Amondarian: Sequence Learning for Medical IoT Data for Predictive Maintainance (MA WI, in coop. with Siemens Healthineers, Tobias Hipp, Gromowski & Schmid, July 2020)
146. Nina Krob: Ausdrucksst?rke und Effizienz in der Generierung von Erkl?rungen: Vergleich von Association Rule Mining und Induktiver Logischer Programmierung für interpretierbare Klassifikation von Schmerz (BA AI, Finzel & Schmid, TraMeExCo, July 2020)
145. Jasmin Fritz: Application of LIME for Transparent Pedestrian Detection (BA AI, Rabold, June 2020)
144. Clemens Bartnik: A Comparison between Visual Saliency Maps of Convolutional Neural Networks and those of Human Beings -- A Study on Facial Expression Recognition (MA Psy, May 2020)
143. Malte Büttner: The Role of Local Versus Global Features in Convolutional Neural Networks: A Comparison of State of the Art Architectures (MA AI, Rabold & Ute Schmid, May 2020)
142. Alexis Thomas: Investigating Explanatory Graphs to Make CNN Classifications Transparent (MA International Software System Science, Johannes Rabold & Ute Schmid, March 2020)
141. Jonas Amling: Explaining Text Classification Decisions with LIME -- Topic-based versus Random Input Manipulation (BA AI, Bruckert & Schmid, March 2020)
140. Sascha Riechel: Meta-Learning Character Recognition on Trajectories from Optical and Inertial Sensors (MA AI, in collaboration with Fraunhofer IIS/LA, January 2020)
139. Kristina Prümer: A Cognitive Tutor Generating Error-Specific Feedback for English Grammar Learning (MA CiTH, December 2019)
138. Manuel Dumdey: Untersuchungen zum Einsatz von Methoden des probablistischen Programmierens für Intelligente Künstliche Spiele-Agenten?(Investigating the use of probabilistic programming in Game AI, MA AI, November 2019)
137. Bettina Finzel: Explanation-guided Constraint Generation for an Inverse Entailment Algorithm (MA AI, TraMeExCo, Sept. 2019)
136. Lisa Schatt: Erkl?rungsgenerierung für Irrelevanz-Klassifikationen in Dateisystemen (MA AI, Siebers & Schmid, Dare2Del, Sept. 2019)
135. Hannah Deininger: Inductive Logic Programming Theories as Explanations for Image Classification: How Number and Semantic Distance of Contrasting Classes Influence Explanation Complexity (MA CitH, Rabold & Schmid, July 2019)
Die Arbeit wurde 2020 mit dem PUSh-Preis der Universit?t Bamberg ausgezeichnet.
134. Daniel Sch?fer: Comparing feature-based, sequential, and logic machine learning approaches for trajectory mining (MA AI, July 2019)
Finalist im MINT Award IT 2019 - NEXT GENERATION MOBILITY von audimax MEDIEN, https://www.mint-award-it.de/
133. Krist Fama: A Learning ChatBot -- Incremental Learning for Advice-Giving (MA AI in coop with Institut f. Rehabilitationsforschung, S. Dibbelt, Siebers und Schmid, July 2019)
132. Simon Kuhn: Identifying Near Misses for Relational Concepts with Graph Matching – Explaining Classifier Decisions of Facial Expressions (BA AI, Finzel & Schmid, July 2019)
131. Simon Hoffmann: Comparing Non-Pretrained Deep Learning Architectures for Subcellular Protein Pattern Classification in Confocal Microscope Images (MA CitH, Rabold & Schmid. May 2019)
130. Mohammad Al-Hiti: Evaluation von Methoden des Maschinellen Lernens für die
Induktion strukturell komplexer probabilistischer Regeln (Evaluation of Machine Learning Methods for the
Induction of Structurally Complex Probabilistic Rules; MA AI, Dare2Del, Siebers & Schmid, April 2019)
129. Julius Mehringer: Evaluating Machine Learning Apporaches for Improving Long Term Forecasts for Many Spare Parts (MA Survey Staistics, with Fraunhofer IIS Nuremberg, March 2019, Sperrvermerk)
128. Ludwig Schallner: Effekt verschiedener Methoden zur Generierung von Superpixeln auf die visuellen Erkl?rungen von LIME (in collaboration with Fraunhofer IIS/EZRT, MA AI, March 2019)
127. Felix Hitzler: Reinforcement Learning to Evaluate Different Branching Heuristics for Constraint Satisfaction Problems (MA CitH, in Kooperation mit CAS Software AG, March 2019)
126. Andreas Wiegand: Rekonstruktion von 3D-Modellen mit Generative Adversarial Networks (collaboration with Fraunhofer IIS/EZRT, MA AI, March 2019)
125. Nataliia Plotnikova: Application of Neuronal Network for Irradiance Prediction for Solar Plants (MA AI, with Siemens AG, Rabold & Schmid, March 2019, Sperrvermerk)
Die Arbeit wurde 2019 mit dem PUSh-Preis der Universit?t Bamberg ausgezeichnet.
124. Maximilian Kukla: Exploring an Approach for Semi-automatic Tuning of an X-ray Scanner (BA AI, joint with Siemens Health Care, Dec. 2018)
123. Harshit Gupta: Explanation Generation from Reasoning Traces (MA IntSoSySci, Dare2Del, Siebers & Schmid, Dec. 2018)
122. Johannes Rabold: Enriching LIME with Inductive Logic Programming: Explaining Deep Learning
Classifiers with Logic Rules in a Companion System Framework (MA AI, Oct. 2018) [pdf]
121. Adrian Schwaiger: