ESANN - RankMe

118 papers

Year	Title / Authors
2020	28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2020, Bruges, Belgium, October 2-4, 2020
2020	3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution. Yi Zhao, Nils Wandel, Magdalena Landl, Andrea Schnepf, Sven Behnke
2020	A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction. Matthias Karlbauer, Sebastian Otte, Hendrik P. A. Lensch, Thomas Scholten, Volker Wulfmeyer, Martin V. Butz
2020	A Real-time PCB Defect Detector Based on Supervised and Semi-supervised Learning. Fan He, Sanli Tang, Siamak Mehrkanoon, Xiaolin Huang, Jie Yang
2020	A Survey of Machine Learning applied to Computer Networks. Alexander Gepperth, Sebastian Rieger
2020	A Systematic Assessment of Deep Learning Models for Molecule Generation. Davide Rigoni, Nicolò Navarin, Alessandro Sperduti
2020	A preconditioned accelerated stochastic gradient descent algorithm. Alexandru Onose, Seyed Iman Mossavat, Henk-Jan H. Smilde
2020	ASAP - A Sub-sampling Approach for Preserving Topological Structures. Abolfazl Taghribi, Kerstin Bunte, Michele Mastropietro, Sven De Rijcke, Peter Tiño
2020	Adapting Random Forests to Cope with Heavily Censored Datasets in Survival Analysis. Tossapol Pomsuwan, Alex Alves Freitas
2020	Adversarial domain adaptation without gradient reversal layer. Aymen Cherif, Hugo Serieys
2020	Adversarials-1 in Speech Recognition: Detection and Defence. Nils Worzyk, Stefan Niewerth, Oliver Kramer
2020	An Empirical Study of Iterative Knowledge Distillation for Neural Network Compression. Sharan Yalburgi, Tirtharaj Dash, Ramya Hebbalaguppe, Srinidhi Hegde, Ashwin Srinivasan
2020	An agile machine learning project in pharma - developing a Mask R-CNN-based web application for bacterial colony counting. Paul Smyth, Tanguy Naets, Gaël de Lannoy, Laurent Sorber
2020	An quantum algorithm for feedforward neural networks tested on existing quantum hardware. Daniele Bajoni, Dario Gerace, Chiara Macchiavello, Francesco Tacchino, Panagiotis Kl. Barkoutsos, Ivano Tavernelli
2020	Anomaly Detection Approach in Cyber Security for User and Entity Behavior Analytics System. Vladimir Muliukha, Alexey Lukashin, Lev V. Utkin, Mikhail Popov, Anna A. Meldo
2020	Approximating Archetypal Analysis Using Quantum Annealing. Sebastian Feld, Christoph Roch, Katja Geirhos, Thomas Gabor
2020	Attacking Model Sets with Adversarial Examples. István Megyeri, István Hegedüs, Márk Jelasity
2020	Automatic Pain Intensity Recognition: Training Set Selection based on Outliers and Centroids. Peter Bellmann, Patrick Thiam, Friedhelm Schwenker
2020	Binary and Multi-label Defect Classification of Printed Circuit Board based on Transfer Learning. George O. de A. Azevedo, Leandro H. de S. Silva, Agostinho A. F. Júnior, Bruno J. T. Fernandes, Sergio C. Oliveira
2020	Biochemical Pathway Robustness Prediction with Graph Neural Networks. Marco Podda, Alessio Micheli, Davide Bacciu, Paolo Milazzo
2020	CNN Encoder to Reduce the Dimensionality of Data Image for Motion Planning. Janderson Ferreira, Agostinho A. F. Júnior, Yves M. Galvão, Bruno J. T. Fernandes, Pablo V. A. Barros
2020	Comparison of Cluster Validity Indices and Decision Rules for Different Degrees of Cluster Separation. Sara Kaczynska, Rebecca Marion, Rainer von Sachs
2020	Compressive Learning of Generative Networks. Vincent Schellekens, Laurent Jacques
2020	Cost-free resolution enhancement in Convolutional Neural Networks for medical image segmentation. Oscar J. Pellicer-Valero, María J. Rupérez-Moreno, José David Martín-Guerrero
2020	Cross-Encoded Meta Embedding towards Transfer Learning. György Kovács, Rickard Brännvall, Johan Öhman, Marcus Liwicki
2020	Deep Learning to Detect Bacterial Colonies for the Production of Vaccines. Paul Smyth, John A. Lee, Gaël de Lannoy, Thomas Beznik
2020	Deep Recurrent Graph Neural Networks. Luca Pasa, Nicolò Navarin, Alessandro Sperduti
2020	Detection of abnormal driving situations using distributed representations and unsupervised learning. Florian Mirus, Terrence C. Stewart, Jörg Conradt
2020	Detection of elementary particles with the WiSARD n-tuple classifier. Pedro Xavier, Massimo De Gregorio, Felipe M. G. França, Priscila M. V. Lima
2020	Do we need hundreds of classifiers or a good feature selection? Laura Morán-Fernández, Verónica Bolón-Canedo, Amparo Alonso-Betanzos
2020	Domain Invariant Representations with Deep Spectral Alignment. Christoph Raab, Peter Meier, Frank-Michael Schleif
2020	Efficient computation of counterfactual explanations of LVQ models. André Artelt, Barbara Hammer
2020	Embedding of FRPN in CNN architecture. Alberto Rossi, Markus Hagenbuchner, Franco Scarselli, Ah Chung Tsoi
2020	Entity-Pair Embeddings for Improving Relation Extraction in the Biomedical Domain. Farrokh Mehryary, Hans Moen, Tapio Salakoski, Filip Ginter
2020	Epistemic Risk-Sensitive Reinforcement Learning. Hannes Eriksson, Christos Dimitrakakis
2020	Equilibrium Propagation for Complete Directed Neural Networks. Matilde Tristany, Sérgio Pequito, Pedro A. Santos, Mário A. T. Figueiredo
2020	Estimating Individual Treatment Effects through Causal Populations Identification. Céline Beji, Eric Benhamou, Michaël Bon, Florian Yger, Jamal Atif
2020	Explaining t-SNE Embeddings Locally by Adapting LIME. Adrien Bibal, Viet Minh Vu, Géraldin Nanfack, Benoît Frénay
2020	Explorations in Quantum Neural Networks with Intermediate Measurements. Lukas Franken, Bogdan Georgiev
2020	Exploring the feature space of character-level embeddings. Ivano Lauriola, Stefano Campese, Alberto Lavelli, Fabio Rinaldi, Fabio Aiolli
2020	Fast Deep Neural Networks Convergence using a Weightless Neural Model. Alan T. L. Bacellar, Brunno F. Goldstein, Victor da Cruz Ferreira, Leandro Santiago, Priscila M. V. Lima, Felipe M. G. França
2020	Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models. Pawel Morawiecki, Przemyslaw Spurek, Marek Smieja, Jacek Tabor
2020	Frontiers in Reservoir Computing. Claudio Gallicchio, Mantas Lukosevicius, Simone Scardapane
2020	Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent. Nicolas Boria, Benjamin Négrevergne, Florian Yger
2020	Gaussian process regression for the estimation of stable univariate time-series processes. Georgios Birpoutsoukis, Julien M. Hendrickx
2020	GraN: An Efficient Gradient-Norm Based Detector for Adversarial and Misclassified Examples. Julia Lust, Alexandru Paul Condurache
2020	Graph Neural Networks for the Prediction of Protein-Protein Interfaces. Niccolò Pancino, Alberto Rossi, Giorgio Ciano, Giorgia Giacomini, Simone Bonechi, Paolo Andreini, Franco Scarselli, Monica Bianchini, Pietro Bongini
2020	Handling missing data in recurrent neural networks for air quality forecasting. Michel Tokic, Anja von Beuningen, Christoph Tietz, Hans-Georg Zimmermann
2020	Image completion via nonnegative matrix factorization using B-splines. Cécile Hautecoeur, François Glineur
2020	Improving Light-weight Convolutional Neural Networks for Face Recognition Targeting Resource Constrained Platforms. Iulian-Ionut Felea, Radu Dogaru
2020	Improving the Union Bound: a Distribution Dependent Approach. Luca Oneto, Sandro Ridella, Davide Anguita
2020	Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control. Manon Flageat, Kai Arulkumaran, Anil A. Bharath
2020	Interpretation of Model Agnostic Classifiers via Local Mental Images. Aluizio Lima Filho, Gabriel P. Guarisa, Leopoldo Lusquino Filho, Luiz F. R. Oliveira, Carlos Alberto Nunes Cosenza, Felipe M. G. França, Priscila M. V. Lima
2020	Invariant Integration in Deep Convolutional Feature Space. Matthias Rath, Alexandru Paul Condurache
2020	Investigating 3D-STDenseNet for Explainable Spatial Temporal Crime Forecasting. Brian Maguire, Faisal Ghaffar
2020	Joint optimization of predictive performance and selection stability. Victor Hamer, Pierre Dupont
2020	Language Grounded Task-Adaptation in Reinforcement Learning. Matthias Hutsebaut-Buysse, Kevin Mets, Steven Latré
2020	Language processing in the era of deep learning. Ivano Lauriola, Alberto Lavelli, Fabio Aiolli
2020	Learning Deep Fair Graph Neural Networks. Luca Oneto, Nicolò Navarin, Michele Donini
2020	Learning Step Size Adaptation in Evolution Strategies. Oliver Kramer
2020	Learning from partially labeled data. Siamak Mehrkanoon, Xiaolin Huang, Johan A. K. Suykens
2020	Linear Graph Convolutional Networks. Nicolò Navarin, Wolfgang Erb, Luca Pasa, Alessandro Sperduti
2020	Locally Adaptive Nearest Neighbors. Jan Philip Göpfert, Heiko Wersing, Barbara Hammer
2020	Lower bounds on the nonnegative rank using a nested polytopes formulation. Julien Dewez, François Glineur
2020	Machine learning framework for control in classical and quantum domains. Archismita Dalal, Eduardo J. Páez, Seyed Shakib Vedaie, Barry C. Sanders
2020	Machine learning in the biopharma industry. Gaël de Lannoy, Thibault Helleputte, Paul Smyth
2020	Mining Temporal Changes in Strengths and Weaknesses of Cricket Players Using Tensor Decomposition. Swarup Ranjan Behera, Vijaya Saradhi Vedula
2020	Missing Image Data Imputation using Variational Autoencoders with Weighted Loss. Ricardo Cardoso Pereira, Joana Cristo Santos, José Pereira Amorim, Pedro Pereira Rodrigues, Pedro Henriques Abreu
2020	Model Variance for Extreme Learning Machine. Fabian Guignard, Mohamed Laib, Mikhail F. Kanevski
2020	Modelling human sound localization with deep neural networks. Kiki van der Heijden, Siamak Mehrkanoon
2020	Modular Length Control for Sentence Generation. Katya Kudashkina, Peter Wittek, Jamie Kiros, Graham W. Taylor
2020	Motion Segmentation using Frequency Domain Transformer Networks. Hafez Farazi, Sven Behnke
2020	Multi-Directional Laplacian Pyramids for Completion of Missing Data Entries. Neta Rabin
2020	MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
2020	Navigational Freespace Detection for Autonomous Driving in Fixed Routes. Aparajit Narayan, Elio Tuci, William Xachiti, Aaron Parsons
2020	New Results on Sparse Autoencoders for Posture Classification and Segmentation. Doreen Jirak, Stefan Wermter
2020	Object-centered Fourier Motion Estimation and Segment-Transformation Prediction. Moritz Wolter, Angela Yao, Sven Behnke
2020	On Feature Selection Using Anisotropic General Regression Neural Network. Federico Amato, Fabian Guignard, Philippe Jacquet, Mikhail F. Kanevski
2020	On Learning a Control System without Continuous Feedback. Georgi Angelov, Bogdan Georgiev
2020	On the long-term learning ability of LSTM LMs. Wim Boes, Robbe Van Rompaey, Lyan Verwimp, Joris Pelemans, Hugo Van hamme, Patrick Wambacq
2020	On-edge adaptive acoustic models: an application to acoustic person presence detection. Lode Vuegen, Peter Karsmakers
2020	Perplexity-free Parametric t-SNE. Francesco Crecchi, Cyril de Bodt, Michel Verleysen, John A. Lee, Davide Bacciu
2020	Predicting low gamma- from lower frequency band activity in electrocorticography. Marc M. Van Hulle, Bob Van Dyck, Benjamin Wittevrongel, Flavio Camarrone, Ine Dauwe, Evelien Carrette, Alfred Meurs, Paul Boon, Dirk Van Roost
2020	Problem Transformation Methods with Distance-Based Learning for Multi-Target Regression. Joonas Hämäläinen, Tommi Kärkkäinen
2020	Pyramidal Graph Echo State Networks. Filippo Maria Bianchi, Claudio Gallicchio, Alessio Micheli
2020	Quantum Machine Learning. José David Martín-Guerrero, Lucas Lamata
2020	Quantum-Inspired Learning Vector Quantization for Classification Learning. Thomas Villmann, Jensun Ravichandran, Alexander Engelsberger, Andrea Villmann, Marika Kaden
2020	Random Projection in supervised non-stationary environments. Moritz Heusinger, Frank-Michael Schleif
2020	Random Signal Cut for Improving Multimodal CNN Robustness of 2D Road Object Detection. Robin Condat, Alexandrina Rogozan, Abdelaziz Bensrhair
2020	Recurrent Feedback Improves Recognition of Partially Occluded Objects. Markus Roland Ernst, Jochen Triesch, Thomas Burwick
2020	Reservoir memory machines. Benjamin Paassen, Alexander Schulz
2020	Respiratory Pattern Recognition from Low-Resolution Thermal Imaging. Salla Aario, Ajinkya Gorad, Miika Arvonen, Simo Särkkä
2020	Resume: A Robust Framework for Professional Profile Learning & Evaluation. Clara Gainon de Forsan de Gabriac, Constance Scherer, Amina Djelloul, Vincent Guigue, Patrick Gallinari
2020	SDOstream: Low-Density Models for Streaming Outlier Detection. Alexander Hartl, Félix Iglesias, Tanja Zseby
2020	Self-Organizing Kernel-based Convolutional Echo State Network for Human Actions Recognition. Gin Chong Lee, Chu Kiong Loo, Wei Shiung Liew, Stefan Wermter
2020	Self-organized dynamic attractors in recurrent neural networks. Benedikt Vettelschoss, Matthias Freiberger, Joni Dambre
2020	Self-organizing maps in manifolds with complex topologies: An application to the planning of closed path for indoor UAV patrols. Hervé Frezza-Buet
2020	Seq-to-NSeq model for multi-summary generation. Guillaume Le Berre, Christophe Cerisara
2020	Sequence Classification using Ensembles of Recurrent Generative Expert Modules. Marius Hobbhahn, Martin V. Butz, Sarah Fabi, Sebastian Otte
2020	Similarities between policy gradient methods in reinforcement and supervised learning. Eric Benhamou, David Saltiel
2020	Simplifying Deep Reservoir Architectures. Claudio Gallicchio, Alessio Micheli, Antonio Sisbarra
2020	Softmax Recurrent Unit: A new type of RNN cell. Lucas Vos, Twan van Laarhoven
2020	Sparse K-means for mixed data via group-sparse clustering. Marie Chavent, Jérôme Lacaille, Alex Mourer, Madalina Olteanu
2020	Sparse Metric Learning in Prototype-based Classification. Johannes Brinkrolf, Barbara Hammer
2020	Tensor Decompositions in Deep Learning. Davide Bacciu, Danilo P. Mandic
2020	Tensor Decompositions in Recursive Neural Networks for Tree-Structured Data. Daniele Castellana, Davide Bacciu
2020	Theoretically Expressive and Edge-aware Graph Learning. Federico Errica, Davide Bacciu, Alessio Micheli
2020	Time Series Prediction using Disentangled Latent Factors. Perrine Cribier-Delande, Raphaël Puget, Vincent Guigue, Ludovic Denoyer
2020	Tournament Selection Improves Cartesian Genetic Programming for Atari Games. Tim Cofala, Lars Elend, Oliver Kramer
2020	Towards Adversarial Attack Resistant Deep Neural Networks. Tiago A. O. Alves, Sandip Kundu
2020	Understanding and improving unsupervised training of Boltzman machines. Przemyslaw R. Grzybowski, Gorka Muñoz-Gil, Alejandro Pozas-Kerstjens, Miguel Ángel García-March, Maciej Lewenstein
2020	Unsupervised Latent Space Translation Network. Magda Friedjungová, Daniel Vasata, Tomás Chobola, Marcel Jirina
2020	Variational MIxture of Normalizing Flows. Guilherme G. P. Freitas Pires, Mário A. T. Figueiredo
2020	Verifying Deep Learning-based Decisions for Facial Expression Recognition. Ines Rieger, Rene Kollmann, Bettina Finzel, Dominik Seuss, Ute Schmid
2020	Visualization of the Feature Space of Neural Networks. Carlos M. Alaíz, Ángela Fernández, José R. Dorronsoro
2020	Weighted Emprirical Risk Minimization: Transfer Learning based on Importance Sampling. Robin Vogel, Mastane Achab, Stéphan Clémençon, Charles Tillier
2020	Why state-of-the-art deep learning barely works as good as a linear classifier in extreme multi-label text classification. Mohammadreza Qaraei, Sujay Khandagale, Rohit Babbar
2020	Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks. Bernardo Pérez Orozco, Stephen J. Roberts