Table of Contents

• TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast ModelsUdo Schlegel, Duy Vo Lam, Daniel A. Keim, Daniel Seebacher. 5-14 [doi]
• Interpretable Models via Pairwise Permutations AlgorithmTroy Maasland, João Pereira, Diogo Bastos, Marcus de Goffau, Max Nieuwdorp, Aeilko H. Zwinderman, Evgeni Levin. 15-25 [doi]
• A Classification of Anomaly Explanation MethodsVéronne Yepmo Tchaghe, Grégory Smits, Olivier Pivert. 26-33 [doi]
• Bringing a Ruler Into the Black Box: Uncovering Feature Impact from Individual Conditional Expectation PlotsAndrew Yeh, Anhthy Ngo. 34-48 [doi]
• Reject and Cascade Classifier with Subgroup Discovery for Interpretable Metagenomic SignaturesMaxence Queyrel, Alexandre Templier, Jean-Daniel Zucker. 49-66 [doi]
• Demystifying Graph Neural Network ExplanationsAnna Himmelhuber, Mitchell Joblin, Martin Ringsquandl, Thomas A. Runkler. 67-75 [doi]
• On the Transferability of Neural Models of Morphological AnalogiesSafa Alsaidi, Amandine Decker, Puthineath Lay, Esteban Marquer, Pierre-Alexandre Murena, Miguel Couceiro. 76-89 [doi]
• Behavior of k-NN as an Instance-Based Explanation MethodChhavi Yadav, Kamalika Chaudhuri. 90-96 [doi]
• Enhancing Performance of Occlusion-Based Explanation Methods by a Hierarchical Search Method on Input ImagesHamed Behzadi-Khormouji, Habib Rostami. 97-104 [doi]
• Post-hoc Counterfactual Generation with Supervised AutoencoderVictor Guyomard, Françoise Fessant, Tassadit Bouadi, Thomas Guyet. 105-114 [doi]
• Differentially Private Learning from Label ProportionsTimon Sachweh, Daniel Boiar, Thomas Liebig. 119-127 [doi]
• Approaches to Uncertainty Quantification in Federated Deep LearningFlorian Linsner, Linara Adilova, Sina Däubener, Michael Kamp, Asja Fischer. 128-145 [doi]
• Optimized Federated Learning on Class-Biased Distributed Data SourcesYongli Mou, Jiahui Geng, Sascha Welten, Chunming Rong, Stefan Decker, Oya Beyan. 146-158 [doi]
• Splitting Algorithms for Federated LearningSaber Malekmohammadi, Kiarash Shaloudegi, Zeou Hu, Yaoliang Yu. 159-176 [doi]
• Migrating Models: A Decentralized View on Federated LearningPéter Kiss, Tomás Horváth. 177-191 [doi]
• The Effects of Randomness on the Stability of Node EmbeddingsTobias Schumacher 0002, Hinrikus Wolf, Martin Ritzert, Florian Lemmerich, Martin Grohe, Markus Strohmaier. 197-215 [doi]
• Graph Homomorphism Features: Why Not Sample?Paul Beaujean, Florian Sikora, Florian Yger. 216-222 [doi]
• Neural Maximum Independent SetThomas Pontoizeau, Florian Sikora, Florian Yger, Tristan Cazenave. 223-237 [doi]
• Fea2Fea: Exploring Structural Feature Correlations via Graph Neural NetworksJiaqing Xie, Rex Ying. 238-257 [doi]
• Web Image Context Extraction with Graph Neural Networks and Sentence Embeddings on the DOM TreeChen Dang, Hicham Randrianarivo, Raphaël Fournier-S'niehotta, Nicolas Audebert. 258-267 [doi]
• Towards Mining Generalized Patterns from RDF Data and a Domain OntologyTomas Martin, Victor Fuentes, Petko Valtchev, Abdoulaye Baniré Diallo, René Lacroix, Maxime Leduc, Mounir Boukadoum. 268-278 [doi]
• Homological Time Series Analysis of Sensor Signals from Power PlantsLuciano Melodia, Richard Lenz. 283-299 [doi]
• Continuous-Discrete Recurrent Kalman Networks for Irregular Time SeriesMona Schirmer, Mazin Eltayeb, Maja Rudolph. 300-305 [doi]
• Adversarial Generation of Temporal Data: A Critique on Fidelity of Synthetic DataAnkur Debnath, Nitish Gupta, Govind Waghmare, Hardik Wadhwa, Siddhartha Asthana, Ankur Arora. 306-321 [doi]
• Towards Precomputed 1D-Convolutional Layers for Embedded FPGAsLukas Einhaus, Chao Qian 0009, Christopher Ringhofer, Gregor Schiele. 327-338 [doi]
• Embedded Face Recognition for Personalized Services in the Assistive RoboticsIris Walter, Jonas Ney, Tim Hotfilter, Vladimir Rybalkin, Julian Höfer, Norbert Wehn, Jürgen Becker 0001. 339-350 [doi]
• FLight: FPGA Acceleration of Lightweight DNN Model Inference in Industrial AnalyticsHassan Ghasemzadeh Mohammadi, Felix Paul Jentzsch, Maurice Kuschel, Rahil Arshad, Sneha Rautmare, Suraj Manjunatha, Marco Platzner, Alexander Boschmann, Dirk Schollbach. 351-362 [doi]
• Exploring Cell-Based Neural Architectures for Embedded SystemsIlja van Ipenburg, Dolly Sapra, Andy D. Pimentel. 363-374 [doi]
• Design Space Exploration of Time, Energy, and Error Rate Trade-offs for CNNs Using Accuracy-Programmable Instruction Set ProcessorsArmin Schuster, Christian Heidorn, Marcel Brand, Oliver Keszöcze, Jürgen Teich. 375-389 [doi]
• Ultra-low Power Machinery Fault Detection Using Deep Neural NetworksSven Nitzsche, Moritz Neher, Stefan von Dosky, Jürgen Becker 0001. 390-396 [doi]
• SPNC: Fast Sum-Product Network InferenceLukas Sommer, Cristian Axenie, Andreas Koch 0001. 397-408 [doi]
• Towards Addressing Noise and Static Variations of Analog Computations Using Efficient RetrainingBernhard Klein, Lisa Kuhn, Johannes Weis, Arne Emmel, Yannik Stradmann, Johannes Schemmel, Holger Fröning. 409-420 [doi]
• The Next Frontier: AI We Can Really TrustAndreas Holzinger. 427-440 [doi]
• This Looks Like That, Because ... Explaining Prototypes for Interpretable Image RecognitionMeike Nauta, Annemarie Jutte, Jesper C. Provoost, Christin Seifert. 441-456 [doi]
• Prototypical Convolutional Neural Network for a Phrase-Based Explanation of Sentiment ClassificationKamil Plucinski, Mateusz Lango, Jerzy Stefanowski. 457-472 [doi]
• Explanations for Network Embedding-Based Link PredictionsBo Kang, Jefrey Lijffijt, Tijl De Bie. 473-488 [doi]
• Exploring Counterfactual Explanations for Classification and Regression TreesSuryabhan Singh Hada, Miguel Á. Carreira-Perpiñán. 489-504 [doi]
• Towards Explainable Meta-learningKatarzyna Woznica, Przemyslaw Biecek. 505-520 [doi]
• How to Choose an Explainability Method? Towards a Methodical Implementation of XAI in PracticeTom Vermeire, Thibault Laugel, Xavier Renard, David Martens, Marcin Detyniecki. 521-533 [doi]
• Using Explainable Boosting Machines (EBMs) to Detect Common Flaws in DataZhi Chen, Sarah Tan, Harsha Nori, Kori Inkpen, Yin Lou, Rich Caruana. 534-551 [doi]
• Algorithmic Factors Influencing Bias in Machine LearningWilliam Blanzeisky, Pádraig Cunningham. 559-574 [doi]
• Desiderata for Explainable AI in Statistical Production Systems of the European Central BankCarlos Mougan Navarro, Georgios Kanellos, Thomas Gottron. 575-590 [doi]
• Robustness of Fairness: An Experimental AnalysisSerafina Kamp, Andong Luis Li Zhao, Sindhu Kutty. 591-606 [doi]
• Co-clustering for Fair RecommendationGabriel Frisch, Jean-Benoist Léger, Yves Grandvalet. 607-630 [doi]
• Learning a Fair Distance Function for Situation TestingDaphne Lenders, Toon Calders. 631-646 [doi]
• Towards Fairness Through TimeAlessandro Castelnovo, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Cosentini. 647-663 [doi]
• Active Inference for Stochastic ControlAswin Paul, Noor Sajid, Manoj Gopalkrishnan, Adeel Razi. 669-680 [doi]
• Towards Stochastic Fault-Tolerant Control Using Precision Learning and Active InferenceMohamed Baioumy, Corrado Pezzato, Carlos Hernández Corbato, Nick Hawes, Riccardo Ferrari. 681-691 [doi]
• On the Convergence of DEM's Linear Parameter EstimatorAjith Anil Meera, Martijn Wisse. 692-700 [doi]
• Disentangling What and Where for 3D Object-Centric Representations Through Active InferenceToon Van de Maele, Tim Verbelen, Ozan Çatal, Bart Dhoedt. 701-714 [doi]
• Rule Learning Through Active Inductive InferenceTore Erdmann, Christoph Mathys. 715-725 [doi]
• Interpreting Dynamical Systems as Bayesian ReasonersNathaniel Virgo, Martin Biehl, Simon McGregor. 726-762 [doi]
• Blankets All the Way up - the Economics of Active InferenceMorten Henriksen. 763-771 [doi]
• Filtered States: Active Inference, Social Media and Mental HealthBen White, Mark Miller. 772-783 [doi]
• Ideas Worth Spreading: A Free Energy Proposal for Cumulative Cultural DynamicsNatalie Kastel, Casper Hesp. 784-798 [doi]
• Dream to Explore: 5-HT2a as Adaptive Temperature Parameter for Sophisticated Affective InferenceAdam Safron, Zahra Sheikhbahaee. 799-809 [doi]
• Inferring in Circles: Active Inference in Continuous State Space Using Hierarchical Gaussian Filtering of Sufficient StatisticsPeter Thestrup Waade, Nace Mikus, Christoph Mathys. 810-818 [doi]
• On Solving a Stochastic Shortest-Path Markov Decision Process as Probabilistic InferenceMohamed Baioumy, Bruno Lacerda, Paul Duckworth, Nick Hawes. 819-829 [doi]
• Habitual and Reflective Control in Hierarchical Predictive CodingPaul F. Kinghorn, Beren Millidge, Christopher L. Buckley. 830-842 [doi]
• Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing ProblemNiels van Hoeffelen, Pablo Lanillos. 843-856 [doi]
• Robot Localization and Navigation Through Predictive Processing Using LiDARDaniel Burghardt, Pablo Lanillos. 857-864 [doi]
• Sensorimotor Visual Perception on Embodied System Using Free Energy PrincipleKanako Esaki, Tadayuki Matsumura, Kiyoto Ito, Hiroyuki Mizuno. 865-877 [doi]