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<TitleText textcase="01">ESANN 2024 - Proceedings</TitleText> 
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<Text textformat="02">&#60;p&#62;&#60;strong&#62;Informed Machine Learning for Complex Data&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Informed Machine Learning for Complex Data&#60;br /&#62;
L. Oneto, N. Navarin, A. Micheli, L. Pasa, C. Gallicchio, D. Bacciu, D. Anguita&#60;/p&#62;
&#60;p&#62;Informed Machine Learning: Excess Risk and Generalization&#60;br /&#62;
L. Oneto, D. Anguita, S. Ridella&#60;/p&#62;
&#60;p&#62;Enhancing Echo State Networks with Gradient-based Explainability Methods&#60;br /&#62;
F. Spinnato, A. Cossu, R. Guidotti, A. Ceni, C. Gallicchio, D. Bacciu&#60;/p&#62;
&#60;p&#62;Generalizing Convolution to Point Clouds&#60;br /&#62;
D. Bacciu, F. Landolfi&#60;/p&#62;
&#60;p&#62;Towards the application of Backpropagation-Free Graph Convolutional Networks on Huge Datasets&#60;br /&#62;
N. Navarin, L. Pasa, A. Sperduti&#60;/p&#62;
&#60;p&#62;Continual Learning with Graph Reservoirs: Preliminary experiments in graph classification&#60;br /&#62;
D. Tortorella, A. Micheli &#60;/p&#62;
&#60;p&#62;XAI and Bias of Deep Graph Networks&#60;br /&#62;
M. Fontanesi, A. Micheli, M. Podda &#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Machine learning in distributed, federated and non-stationery environments&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Machine learning in distributed, federated and non-stationary environments &#8211; recent trends&#60;br /&#62;
M. Polato, B. Hammer, F.-M. Schleif&#60;/p&#62;
&#60;p&#62;Sparse Uncertainty-Informed Sampling from Federated Streaming Data&#60;br /&#62;
M. Röder, F.-M. Schleif &#60;/p&#62;
&#60;p&#62;On the Fine Structure of Drifting Features&#60;br /&#62;
F. Hinder, V. Vaquet, B. Hammer &#60;/p&#62;
&#60;p&#62;FedHP: Federated Learning with Hyperspherical Prototypical Regularization&#60;br /&#62;
S. Fonio, M. Polato, R. Esposito&#60;/p&#62;
&#60;p&#62;Few-shot similarity learning for motion classification via electromyography&#60;br /&#62;
R. Liu, B. Paassen &#60;/p&#62;
&#60;p&#62;About Vector Quantization and its Privacy in Federated Learning&#60;br /&#62;
R. Schubert, T. Villmann &#60;/p&#62;
&#60;p&#62;Federated Time Series Classification with ROCKET features&#60;br /&#62;
B. Casella, M. Jakobs, M. Aldinucci, S. Buschjäger&#60;/p&#62;
&#60;p&#62;Federated Learning in a Semi-Supervised Environment for Earth Observation Data&#60;br /&#62;
B. Casella, A. B. Chisari, M. Aldinucci, S. Battiato, M. V. Giuffrida&#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Continual Improvement of Deep Neural Networks in The Age of Big Data&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Continual Learning of Deep Neural Networks in The Age of Big Data&#60;br /&#62;
A. Gepperth, T. Lesort&#60;/p&#62;
&#60;p&#62;Sequential Continual Pre-Training for Neural Machine Translation&#60;br /&#62;
N. Dalla Noce, M. Resta, D. Bacciu &#60;/p&#62;
&#60;p&#62;Towards Deep Continual Workspace Monitoring: Performance Evaluation of CL Strategies for Object Detection in Working Sites&#60;br /&#62;
A. Celik, O. Urhan, A. Cossu, V. Lomonaco&#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Optimization&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Joint Entropy Search for Multi-objective Bayesian Optimization with Constraints and Multiple Fidelities&#60;br /&#62;
D. Fernández-Sánchez, D. Hernández-Lobato&#60;/p&#62;
&#60;p&#62;Convergence analysis of an inexact gradient method on smooth convex functions&#60;br /&#62;
P. Vernimmen, F. Glineur&#60;/p&#62;
&#60;p&#62;ADLER - An efficient Hessian-based strategy for adaptive learning rate&#60;br /&#62;
D. Balboni, D. Bacciu &#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Classification and regression&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Automatic Miscalibration Diagnosis: Interpreting Probability Integral Transform (PIT) Histograms&#60;br /&#62;
O. Podsztavek, A. I. Jordan, P. Tvrdík, K. L. Polsterer&#60;br /&#62;
&#60;br /&#62;
Feature Learning using Multi-view Kernel Partial Least Squares&#60;br /&#62;
X. Zeng, Q. Tao, J. Suykens&#60;/p&#62;
&#60;p&#62;Stable Diffusion Dataset Generation for Downstream Classification Tasks&#60;br /&#62;
E. Lomurno, M. D'Oria, M. Matteucci&#60;/p&#62;
&#60;p&#62;Extrapolating Venusian Atmospheric Profiles using MAGMA Gaussian Processes&#60;br /&#62;
S. Lejoly, A. Piccialli, A. Mahieux, A. C. Vandaele, B. Frénay&#60;/p&#62;
&#60;p&#62;Antagonism between Classification and Reconstruction Processes in Deep Predictive Coding Networks&#60;br /&#62;
J. Rathjens, L. Wiskott &#60;/p&#62;
&#60;p&#62;Constraints as Alternative Learning Objective in Deep Learning&#60;br /&#62;
Q. Van Baelen, P. Karsmakers&#60;/p&#62;
&#60;p&#62;CNNGen: A Generator and a Dataset for Energy-Aware Neural Architecture Search&#60;br /&#62;
A. Gratia, H. Liu, S. Satoh, P. Temple, P.-Y. Schobbens, G. Perrouin&#60;/p&#62;
&#60;p&#62;Adversarial Training without Hard Labels&#60;br /&#62;
A. Al-Najjar, I. Megyeri, M. Jelasity&#60;/p&#62;
&#60;p&#62;Learning Kernel Parameters for Support Vector Classification Using Similarity Embeddings&#60;br /&#62;
A. P. Braga, M. Menezes, L. Torres&#60;/p&#62;
&#60;p&#62;Causes of Rejects in Prototype-based Classification Aleatoric vs. Epistemic Uncertainty&#60;br /&#62;
J. Brinkrolf, V. Vaquet, F. Hinder, B. Hammer &#60;/p&#62;
&#60;p&#62;''Mental Images'' driven classification&#60;br /&#62;
G. Coda, M. De Gregorio, A. Sorgente, P. Vanacore&#60;/p&#62;
&#60;p&#62;Transfer learning to minimize the predictive risk in clinical research&#60;br /&#62;
S. Branders, J. Paul, A. Ooghe, A. Pereira&#60;/p&#62;
&#60;p&#62;Leveraging performance-based metadata for designing multi-objective NAS strategies for efficient models in Earth Observation.&#60;br /&#62;
E. Demir, R. Traoré, A. Camero&#60;/p&#62;
&#60;p&#62;AI-based algorithm for intrusion detection on a real dataset&#60;br /&#62;
D. Esteban Martínez, B. Guijarro-Berdiñas, A. Alonso Betanzos, E. Hernández-Pereira, A. Esteban Martínez &#60;/p&#62;
&#60;p&#62;Similarity-Based Zero-Shot Domain Adaptation for Wearables&#60;br /&#62;
M. Vieth, N. Grimmelsmann, A. Schneider, B. Hammer&#60;/p&#62;
&#60;p&#62;Robustness and Regularization in Hierarchical Re-Basin&#60;br /&#62;
B. Franke, F. Heinrich, M. Lange, A. Raulf &#60;/p&#62;
&#60;p&#62;Lightweight Cross-Modal Representation Learning&#60;br /&#62;
B. Faye, H. Azzag, M. Lebbah, D. Bouchaffra&#60;/p&#62;
&#60;p&#62;Human Activity Recognition from Thigh and Wrist Accelerometry&#60;br /&#62;
A. Castellanos Alonso, A. López, D. Garcia-Perez, D. Álvarez, J. C. Alvarez &#60;/p&#62;
&#60;p&#62;On F&#946;-score and Cost-Consistency in Evaluation of Imbalanced Classification&#60;br /&#62;
A. Avela&#60;/p&#62;
&#60;p&#62;Decision fusion based multimodal hierarchical method for speech emotion recognition from audio and text&#60;br /&#62;
N. Alqurashi, Y. Li, K. Sidorov, D. Marshall &#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Trust in Artificial Intelligence: Beyond Interpretability&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Trust in Artificial Intelligence: Beyond Interpretability&#60;br /&#62;
T. Bouadi, B. Frénay, L. Galárraga, P. Geurts, B. Hammer, G. Perrouin&#60;/p&#62;
&#60;p&#62;Interpreting Hybrid AI through Autodecoded Latent Space Entities&#60;br /&#62;
R. Veen, C. Hadjichristodoulou, M. Biehl &#60;/p&#62;
&#60;p&#62;ProtoNCD: Prototypical Parts for Interpretable Novel Class Discovery&#60;br /&#62;
T. Michalski, D. Rymarczyk, D. Barczyk, B. Zieli&#324;ski &#60;/p&#62;
&#60;p&#62;Evaluating the Quality of Saliency Maps for Distilled Convolutional Neural Networks&#60;br /&#62;
J. Wilfling, M. Valdenegro-Toro, M. Zullich&#60;/p&#62;
&#60;p&#62;Safety-Oriented Pruning and Interpretation of Reinforcement Learning Policies&#60;br /&#62;
D. Gross, H. Spieker&#60;/p&#62;
&#60;p&#62;Evaluation methodology for disentangled uncertainty quantification on regression models&#60;br /&#62;
K. Pasini, C. Arlotti, M. Leyli Abadi, M. Nabhan, J. Baro &#60;/p&#62;
&#60;p&#62;Influence of Data Characteristics on Machine Learning Classification&#60;br /&#62;
Performance and Stability of SHapley Additive exPlanations&#60;br /&#62;
A. Ihalapathirana, G. Chandra, P. Lavikainen, P. Siirtola, S. Tamminen, N. Talukder, J. Martikainen, J. Röning&#60;br /&#62;
&#60;br /&#62;
Insight-SNE: Understanding t-SNE Embeddings through Interactive Explanation&#60;br /&#62;
S. Corbugy, T. Septon, B. Dumas, B. Frénay&#60;/p&#62;
&#60;p&#62;Does a Reduced Fine-Tuning Surface Impact the Stability of the Explanations of LLMs?&#60;br /&#62;
J. Bogaert, F.-X. Standaert&#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Nonlinear dimensionality reduction and unsupervised learning&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Positive and Scale Invariant Gaussian Process Latent Variable Model for&#60;br /&#62;
Astronomical Spectra&#60;br /&#62;
N. Gianniotis, K. L. Polsterer, I. I. Cortés Pérez&#60;/p&#62;
&#60;p&#62;Forget early exaggeration in t-SNE: early hierarchization preserves global structure&#60;br /&#62;
J. Lee, E. Couplet, P. Lambert, L. Journaux, D. Mulders, C. de Bodt,&#60;br /&#62;
M. Verleysen &#60;/p&#62;
&#60;p&#62;Estimated neighbour sets and smoothed sampled global interactions are sufficient for a fast approximate tSNE.&#60;br /&#62;
P. Lambert, E. Couplet, C. de Bodt, J. Lee&#60;/p&#62;
&#60;p&#62;Hyperbolic Metabolite-Disease Association Prediction&#60;br /&#62;
D. Pogány, P. Antal &#60;/p&#62;
&#60;p&#62;Interactive Machine Learning-Powered Dashboard for Energy Analytics in Residential Buildings&#60;br /&#62;
D. Garcia-Perez, I. Diaz-Blanco, J. M. Enguita-Gonzalez, J. Menéndez, A. A. Cuadrado-Vega &#60;/p&#62;
&#60;p&#62;Exploring Self-Organizing Maps for Addressing Semantic Impairments&#60;br /&#62;
J. Graneri, S. Basterrech, G. Rubino, E. Mizraji &#60;/p&#62;
&#60;p&#62;HDBSCAN for 3-rd order tensor&#60;br /&#62;
D. F. Andriantsiory, J. Ben Geloun, M. Lebbah &#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Graph learning&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Large-Scale Continuous Structure Learning from Time-Series Data&#60;br /&#62;
F. Michelis, R. Massidda, D. Bacciu &#60;/p&#62;
&#60;p&#62;Noise Robust One-Class Intrusion Detection on Dynamic Graphs&#60;br /&#62;
A. Liuliakov, A. Schulz, L. Hermes, B. Hammer&#60;br /&#62;
&#60;br /&#62;
SAT Instances Generation Using Graph Variational Autoencoders&#60;br /&#62;
D. Crowley, M. Dalla, B. O'Sullivan, A. Visentin &#60;/p&#62;
&#60;p&#62;Dual Stream Graph Transformer Fusion Networks for Enhanced Brain Decoding&#60;br /&#62;
L. Goené, S. Mehrkanoon&#60;/p&#62;
&#60;p&#62;Link prediction heuristics for temporal graph benchmark&#60;br /&#62;
M. Dileo, M. Zignani &#60;/p&#62;
&#60;p&#62;Inductive lateral movement detection in enterprise computer networks&#60;br /&#62;
C. Larroche&#60;/p&#62;
&#60;p&#62;T-WinG: Windowing for Temporal Knowledge Graph Completion&#60;br /&#62;
N.-T. Nguyen, T. Vu, T. Le &#60;/p&#62;
&#60;p&#62;Exploring Temporal Knowledge Graphs with Compositional Interactions and Diachronic Mechanisms&#60;br /&#62;
L. Tran, B. Le, T. Le &#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Domain Knowledge Integration in Machine Learning Systems&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Domain Knowledge Integration in Machine Learning Systems - An Introduction&#60;br /&#62;
M. Kaden, S. Saralajew, T. Villmann&#60;/p&#62;
&#60;p&#62;Tumor Grading via Decorrelated Sparse Survival Regression&#60;br /&#62;
B. Paassen, N. Gaisa, M. Rose, M.-S. Bösherz&#60;/p&#62;
&#60;p&#62;Physics-Aware Normalizing Flows: Leveraging Electric Circuit Models in Adversarial Learning&#60;br /&#62;
B. Schindler, T. Schmid&#60;/p&#62;
&#60;p&#62;Leveraging Physics-Informed Neural Networks as Solar Wind Forecasting Models&#60;br /&#62;
N. Costa, F. S. Barros, J. J. G. Lima, R. F. Pinto, A. Restivo&#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Online learning and concept drift&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Self-Supervised Learning from Gradually Drifting Data Streams&#60;br /&#62;
V. Vaquet, J. Vaquet, F. Hinder, K. Malialis, C. Panayiotou, M. Polycarpou, B. Hammer&#60;/p&#62;
&#60;p&#62;On-line Learning Dynamics in Layered Neural Networks with Arbitrary&#60;br /&#62;
Activation Functions&#60;br /&#62;
F. Richert, O. Citton, M. Biehl&#60;/p&#62;
&#60;p&#62;Online Adaptation of Compressed Models by Pre-Training and Task-Relevant Pruning&#60;br /&#62;
T. Avé, M. Hutsebaut-Buysse, W. Wei, K. Mets&#60;/p&#62;
&#60;p&#62;Deep Temporal Consensus Clustering for Patient Stratification in Amyotrophic Lateral Sclerosis&#60;br /&#62;
M. Pego Roque, A. S. Martins, M. Gromicho, M. de Carvalho, S. C. Madeira, P. Tomás, H. Aidos &#60;/p&#62;
&#60;p&#62;Trustworthiness Score for Echo State Networks by Analysis of the Reservoir Dynamics&#60;br /&#62;
J. M. Enguita-Gonzalez, D. Garcia-Perez, A. A. Cuadrado-Vega, D. García-Peña, J. R. Rodríguez-Ossorio, I. Diaz-Blanco &#60;/p&#62;
&#60;p&#62;Invariant Representation Learning for Generalizable Imitation&#60;br /&#62;
M. Jabri, P. Papadakis, E. Abbasnejad, G. Coppin, J. Shi&#60;/p&#62;
&#60;p&#62;Unsupervised Drift Detection Using Quadtree Spatial Mapping&#60;br /&#62;
B. A. Ramos, C. Leite de Castro, T. A. Coelho, P. Angelov &#60;br /&#62;
Time series, recurrent and reinforcement learning&#60;/p&#62;
&#60;p&#62;LSTM encoder-decoder model for contextualized time series forecasting applied to the simulation of a digital patient's physiological variables&#60;br /&#62;
J. Paris, C. Sinoquet, F. Taia-Alaoui, C. Lejus-Bourdeau&#60;/p&#62;
&#60;p&#62;Reservoir Memory Networks&#60;br /&#62;
C. Gallicchio, A. Ceni &#60;/p&#62;
&#60;p&#62;Why long model-based rollouts are no reason for bad Q-value estimates&#60;br /&#62;
P. Wissmann, D. Hein, S. Udluft, V. Tresp&#60;/p&#62;
&#60;p&#62;Recurrent Neural Network based Counter Automata&#60;br /&#62;
S. Leal, L. Lago&#60;/p&#62;
&#60;p&#62;Multidimensional CDTW-based features for Parkinson's Disease classification&#60;br /&#62;
F. Attal, N. Khoury, Y. Amirat&#60;/p&#62;
&#60;p&#62;Vision Language Models as Policy Learners in Reinforcement Learning Environments&#60;br /&#62;
G. Bonetta, D. Zago, R. Cancelliere, M. Polato, B. Magnini&#60;/p&#62;
&#60;p&#62;Predicting the Closing Cross Auction Results at the NASDAQ Stock Exchange&#60;br /&#62;
S. Cohen, M. Hettich, P. Bielefeld, C. Schomers, T. Friedrich&#60;/p&#62;
&#60;p&#62;A Deep Double Q-Learning as a SDLS support in solving LABS problem&#60;br /&#62;
D. &#379;urek &#60;/p&#62;
&#60;p&#62;Enhanced Deep Reinforcement Learning based Group Recommendation System with Multi-head Attention for Varied Group Sizes&#60;br /&#62;
S. Izadkhah, B. Rekabdar &#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Aeronautic data analysis&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Aeronautic data analysis&#60;br /&#62;
J. Lacaille, P. Fabiani, P. Besson &#60;/p&#62;
&#60;p&#62;From Data to Simulation: Capturing Aircraft Engine Degradation Dynamics&#60;br /&#62;
A. Madane, F. Forest, H. Azzag, M. Lebbah, J. Lacaille&#60;/p&#62;
&#60;p&#62;A Kalman Filter and Neural Network Hybrid Approach for Health Monitoring of Aircraft Engines&#60;br /&#62;
S. Thépaut, S. Razakarivony, D. Q. Vu, A. Bauny&#60;/p&#62;
&#60;p&#62;Towards Contrail Mitigation through Robustand Frugal AI-Driven Data Exploitation&#60;br /&#62;
D. Di Giusto, G. Boussu, S. Alix, C. Reverdy, M. Riou, T. Petrisor&#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Modern Machine Learning Methods for robust and real-time Brain-Computer Interfaces (BCI)&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;Machine Learning Methods for BCI: challenges, pitfalls and promises&#60;br /&#62;
J. A. Riascos, M. Molinas, F. Lotte&#60;/p&#62;
&#60;p&#62;Exploring High- and Low-Density Electroencephalography for a Dream&#60;br /&#62;
Decoding Brain-Computer Interface&#60;br /&#62;
M. Packiyanathan, A. Torvestad, M. Molinas, L. A. Moctezuma Pascual &#60;/p&#62;
&#60;p&#62;Deep Riemannian Neural Architectures for Domain Adaptation in Burst&#60;br /&#62;
cVEP-based Brain Computer Interface&#60;br /&#62;
S. Velut, S. Chevallier, M.-C. Corsi, F. Dehais&#60;/p&#62;
&#60;p&#62;EEG Source Imaging Enhances Motor Imagery Classification&#60;br /&#62;
A. Soler, V. Naas, A. Giri, M. Molinas&#60;br /&#62;
Unveiling Dreams: Moving Towards Automatic Dream Decoding via qualitative EEG Analysis and Machine Learning&#60;br /&#62;
A. Torvestad, M. Packiyanathan, L. A. Moctezuma Pascual, M. Molinas&#60;/p&#62;
&#60;p&#62;Towards calibration-free online EEG motor imagery decoding using Deep Learning&#60;br /&#62;
M. Wimpff, J. Zerfowski, B. Yang&#60;br /&#62;
&#60;br /&#62;
Geometric Deep Learning to Enhance Imbalanced Domain Adaptation in EEG&#60;br /&#62;
S. Li, M. Kawanabe, R. Kobler&#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Language models&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;LLaMA Tunes CMA-ES&#60;br /&#62;
O. Kramer&#60;/p&#62;
&#60;p&#62;A Two-Stage Approach for Implicit Bias Detection in Generative Language Models&#60;br /&#62;
J. Edwards, R. Hu, A. Lendasse, A. Schlager, P. Lindner&#60;/p&#62;
&#60;p&#62;Fine-Tuning Llama 2 Large Language Models for Detecting Online Sexual&#60;br /&#62;
Predatory Chats and Abusive Texts&#60;br /&#62;
T. T. Nguyen, C. Wilson, J. Dalins&#60;/p&#62;
&#60;p&#62;Towards Explainable Evolution Strategies with Large Language Models&#60;br /&#62;
J. Baumann, O. Kramer&#60;/p&#62;
&#60;p&#62;Embodying Language Models in Robot Action&#60;br /&#62;
C. Gäde, O. Özdemir, C. Weber, S. Wermter&#60;/p&#62;
&#60;p&#62;Large Language Models as Tuning Agents of Metaheuristics&#60;br /&#62;
A. Martinek, S. &#321;ukasik, A. H. Gandomi&#60;/p&#62;
&#60;p&#62;ChatDT: Simplifying Constraint Integration in Decision Trees&#60;br /&#62;
A. P. Chokki, B. Frénay&#60;/p&#62;
&#60;p&#62;&#60;strong&#62;Image processing and computer vision&#60;/strong&#62;&#60;/p&#62;
&#60;p&#62;From Three to Two Dimensions: 2D Quaternion Convolutions for 3D Images&#60;br /&#62;
V. Delchevalerie, B. Frénay, A. Mayer&#60;/p&#62;
&#60;p&#62;Visualizing and Improving 3D Mesh Segmentation with DeepView&#60;br /&#62;
A. Mazur, I. Roberts, D. Leins, A. Schulz, B. Hammer&#60;/p&#62;
&#60;p&#62;Clarity: a Deep Ensemble for Visual Counterfactual Explanations&#60;br /&#62;
C. Theobald, F. Pennerath, B. Conan-Guez, M. Couceiro, A. Napoli &#60;/p&#62;
&#60;p&#62;An Efficient Neural Architecture Search Model for Medical Image Classification&#60;br /&#62;
L. Xie, E. Lomurno, M. Gambella, D. Ardagna, M. Roveri, M. Matteucci, Q. Shi &#60;/p&#62;
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R. Ghyselinck, J. Fink, B. Dumas, B. Frénay&#60;/p&#62;
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D. Björnberg, M. Ericsson, W. Löwe, J. Nordqvist &#60;/p&#62;
&#60;p&#62;Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks&#60;br /&#62;
Y. Zhang, D. Soydaner, F. Behrad, L. Koßmann, J. Wagemans&#60;/p&#62;
&#60;p&#62;Influence of image encoders and image features transformations in emergent communication&#60;br /&#62;
B. Vanderplaetse, S. Dupont, X. Siebert&#60;/p&#62;
&#60;p&#62;SDE U-Net: Disentangling Aleatoric and Epistemic Uncertainties in Medical Image Segmentation&#60;br /&#62;
C. Zhang, A. M. Barragan Montero, J. Lee&#60;/p&#62;
&#60;p&#62;Generation of Simulated Dataset of Computed Tomography Images of Eggs and Extraction of Measurements Using Deep Learning&#60;br /&#62;
J. P. B. López Vargas, D. Duarte de Paula, D. Salvadeo, E. Bergamim Júnior&#60;/p&#62;
&#60;p&#62;AI-based Collimation Optimization for X-Ray Imaging using Time-of-Flight Cameras&#60;br /&#62;
D. Mairhöfer, M. Laufer, L. Berkel, A. Bischof, E. Barth, J. Barkhausen, T. Martinetz &#60;/p&#62;
&#60;p&#62;On the Stability of Neural Segmentation in Radiology&#60;br /&#62;
M. Wolter, L. Veeramacheneni, B. Baeßler, U. I. Attenberger, B. D. Wichtmann &#60;/p&#62;
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I. Diaz-Blanco, J. M. Enguita-Gonzalez, D. Garcia-Perez, A. A. Cuadrado-Vega, N. Valdes-Gallego, M. D. Chiara-Romero &#60;/p&#62;
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N. Yang, R. Verschuren, C. De Vleeschouwer &#60;/p&#62;
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&#60;p&#62;J. Cristo Santos, M. Seoane Santos, P. Henriques Abreu &#60;/p&#62;
&#60;p&#62;Author index&#60;/p&#62;
&#60;p&#62;Committees &#60;/p&#62;</Text>
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