ESANN

Publications

2023

Mehrdad Mohannazadeh Bakhtiari, Daniel Staps, Thomas Villmann
Learning Vector Quantization in Context of Information Bottleneck Theory. ESANN (2023)
Leopoldo Lusquino Filho, Felipe M. G. França, Priscila Lima
WiSARD-based Ensemble Learning. ESANN (2023)
Alexander Engelsberger, Thomas Villmann
Quantum-ready vector quantization: Prototype learning as a binary optimization problem. ESANN (2023)
Mariya Shumska, Kerstin Bunte
Multispectral Texture Classification in Agriculture. ESANN (2023)
Domenico Tortorella, Alessio Micheli
Richness of Node Embeddings in Graph Echo State Networks. ESANN (2023)
Weiwei Wang, Stefano Bromuri, Michel Dumontier
Graph-based Categorical Embedding. ESANN (2023)
Luca Oneto, Sandro Ridella, Davide Anguita
Towards Randomized Algorithms and Models that We Can Trust: a Theoretical Perspective. ESANN (2023)
Frederieke Richert, Michiel Straat, Elisa Oostwal, Michael Biehl
Layered Neural Networks with GELU Activation, a Statistical Mechanics Analysis. ESANN (2023)
Gianluca Coda, Massimo De Gregorio, Antonio Sorgente, Paolo Vanacore
Improving the DRASiW performance by exploiting its own "Mental Images". ESANN (2023)
Paul Moggridge, Na Helian, Yi Sun, Mariana Lilley
On Instance Weighted Clustering Ensembles. ESANN (2023)
Romain Egele, Isabelle Guyon, Yixuan Sun, Prasanna Balaprakash
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization? ESANN (2023)
Pierre Lambert, John A. Lee, Edouard Couplet, Cyril de Bodt
Nesterov momentum and gradient normalization to improve t-SNE convergence and neighborhood preservation, without early exaggeration. ESANN (2023)
Fatoumata Dama, Christine Sinoquet, Corinne Lejus-Bourdeau
A hidden Markov model with Hawkes process-derived contextual variables to improve time series prediction. Case study in medical simulation. ESANN (2023)
Karan Bhanot, Dennis Wei, Ioana Baldini, Kristin P. Bennett
Adversarial Auditing of Machine Learning Models under Compound Shift. ESANN (2023)
Anne-Sophie Collin, Cyril de Bodt, Dounia Mulders, Christophe De Vleeschouwer
Don't skip the skips: autoencoder skip connections improve latent representation discrepancy for anomaly detection. ESANN (2023)
Danilo Franco, Luca Oneto, Davide Anguita
Mitigating Robustness Bias: Theoretical Results and Empirical Evidences. ESANN (2023)
Samuele Fonio, Lorenzo Paletto, Mattia Cerrato, Dino Ienco, Roberto Esposito
Hierarchical priors for Hyperspherical Prototypical Networks. ESANN (2023)
Alexandra-Ioana Albu
Temporal Ensembling-based Deep k-Nearest Neighbours for Learning with Noisy Labels. ESANN (2023)
Oliver Kramer, Jill Baumann
Wind Power Prediction with ETSformer. ESANN (2023)
Sédrick Stassin, Otmane Amel, Sidi Ahmed Mahmoudi, Xavier Siebert
Similarity versus Supervision: Best Approaches for HS Code Prediction. ESANN (2023)
Sukanya Patra, Le Thi Khanh Hien, Souhaib Ben Taieb
Anomaly detection in irregular image sequences for concentrated solar power plants. ESANN (2023)
Andreas Papachristodoulou, Christos Kyrkou, Stelios Timotheou, Theocharis Theocharides
Introducing Convolutional Channel-wise Goodness in Forward-Forward Learning. ESANN (2023)
Jérôme Fink, Mathieu De Coster, Joni Dambre, Benoît Frénay
Trends and Challenges for Sign Language Recognition with Machine Learning. ESANN (2023)
Alex Rast, Mario Antoine Aoun, Eleni Elia, Nigel T. Crook
Efficient Learning in Spiking Models. ESANN (2023)
Mohammed Aldosari, John A. Miller
On Transformer Autoregressive Decoding for Multivariate Time Series Forecasting. ESANN (2023)
Thomas Villmann, Ronny Schubert, Marika Kaden
Variants of Neural Gas for Regression Learning. ESANN (2023)
Antoine Hubermont, Elio Tuci, Nicola De Quattro
Simultaneous failures classification in a predictive maintenance case. ESANN (2023)
Nigel T. Crook, Alex Rast, Eleni Elia, Mario Antoine Aoun
Functional Resonant Synaptic Clusters for Decoding Time-Structured Spike Trains. ESANN (2023)
Samuel Suárez-Marcote, Laura Morán-Fernández, Verónica Bolón-Canedo
Logarithmic division for green feature selection: an information-theoretic approach. ESANN (2023)
Lee Kezar, Tejas Srinivasan, Riley Carlin, Jesse Thomason, Zed Sevcikova Sehyr, Naomi Caselli
Exploring Strategies for Modeling Sign Language Phonology. ESANN (2023)
Joakim Linja, Joonas Hämäläinen, Tommi Kärkkäinen
Feature Selection for Multi-label Classification with Minimal Learning Machine. ESANN (2023)
Javier Martinez Rodriguez, Martha A. Larson, Louis ten Bosch
Exploring the Importance of Sign Language Phonology for a Deep Neural Network. ESANN (2023)
Otávio Oliveira Napoli, Ana Maria de Almeida, José Miguel Sales Dias, Luís Brás Rosário, Edson Borin, Maurício Breternitz Jr.
Efficient Knowledge Aggregation Methods for Weightless Neural Networks. ESANN (2023)
Leandro H. de S. Silva, Agostinho A. F. Júnior, Bruno J. T. Fernandes, George O. de A. Azevedo, Sergio C. Oliveira
Evaluation of Contrastive Learning for Electronic Component Detection. ESANN (2023)
Maximilian Münch, Katrin Sophie Bohnsack, Alexander Engelsberger, Frank-Michael Schleif, Thomas Villmann
Sparse Nyström Approximation for Non-Vectorial Data Using Class-informed Landmark Selection. ESANN (2023)
Daniel Nowak Assis
Learning with Boosting Decision Stumps for Feature Selection in Evolving Data Streams. ESANN (2023)
Afonso Lourenço, Carolina Ferraz, Jorge Meira, Goreti Marreiros, Verónica Bolón-Canedo, Amparo Alonso-Betanzos
Automated green machine learning for condition-based maintenance. ESANN (2023)
Henda Boudegga, Yaroub Elloumi, Asma Ben Abdallah, Rostom Kachouri, Mouhamed Hédi Bedoui
Retinal blood vessel segmentation from high resolution fundus image using deep learning architecture. ESANN (2023)
Benoît Frénay
A Counterexample to Ockham's Razor and the Curse of Dimensionality: Marginalising Complexity and Dimensionality for GMMs. ESANN (2023)
Alvaro Leandro Cavalcante Carneiro, Denis Henrique Pinheiro Salvadeo, Lucas de Brito Silva
Large-scale dataset and benchmarking for hand and face detection focused on sign language. ESANN (2023)
Yichun Li, Yuxing Yang, Rajesh Nair, Syed Mohsen Naqvi
Action-Based ADHD Diagnosis in Video. ESANN (2023)
M. Lautaro Hickmann, Arne P. Raulf, Frank Köster, Friedhelm Schwenker, Hans-Martin Rieser
Potential analysis of a Quantum RL controller in the context of autonomous driving. ESANN (2023)
Leonardo Amato, Marta Maschietto, Alessandro Leparulo, Mattia Tambaro, Stefano Vassanelli, Alessandro Sperduti
Real-time Detection of Evoked Potentials by Deep Learning: a Case Study. ESANN (2023)
Felix Weiske, Jens Jäkel
Robust and Cheap Safety Measure for Exoskeletal Learning Control with Estimated Uniform PAC (EUPAC). ESANN (2023)
Karol Struniawski, Aleksandra Konopka, Ryszard Kozera
Performance Evaluation of Activation Functions in Extreme Learning Machine. ESANN (2023)
Louis Le Coeur, Nick Riedman, Saarthak Sarup, Kwabena Boahen
Energy-efficient detection of a spike sequence. ESANN (2023)
Adrian Alan Pol, Ekaterina Govorkova, Sonja Grönroos, Nadezda Chernyavskaya, Philip C. Harris, Maurizio Pierini, Isobel Ojalvo, Peter Elmer
Knowledge Distillation for Anomaly Detection. ESANN (2023)
Giulia Marchello, Marco Corneli, Charles Bouveyron
Deep dynamic co-clustering of streams of count data: a new online Zip-dLBM. ESANN (2023)
David Pape, Sina Däubener, Thorsten Eisenhofer, Antonio Emanuele Cinà, Lea Schönherr
On the Limitations of Model Stealing with Uncertainty Quantification Models. ESANN (2023)
Quoc-Huy Trinh, Hieu Nguyen, Van Nguyen, Xuan-Mao Nguyen, Hai-Dang Nguyen
Graph for Transformer Feature: A New Approach for Face Anti-Spoofing. ESANN (2023)