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ORCID28th ICANN 2019: Munich, Germany - Workshop and Special Sessions
- Igor V. Tetko
, Vera Kurková, Pavel Karpov, Fabian J. Theis:
Artificial Neural Networks and Machine Learning - ICANN 2019 - 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17-19, 2019, Proceedings - Workshop and Special Sessions. Lecture Notes in Computer Science 11731, Springer 2019, ISBN 978-3-030-30492-8
Workshop: Reservoir Computing - Methodology
- Stephan Tietz, Doreen Jirak, Stefan Wermter:
A Reservoir Computing Framework for Continuous Gesture Recognition. 7-18 - Anthony Strock, Nicolas P. Rougier, Xavier Hinaut:
Using Conceptors to Transfer Between Long-Term and Short-Term Memory. 19-23 - Felix Meyer zu Driehausen, Rüdiger Busche, Johannes Leugering, Gordon Pipa:
Bistable Perception in Conceptor Networks. 24-34 - Taisuke Kobayashi, Toshiki Sugino:
Continual Learning Exploiting Structure of Fractal Reservoir Computing. 35-47 - Giuseppe Franco, Luca Cerina, Claudio Gallicchio, Alessio Micheli, Marco Domenico Santambrogio:
Continuous Blood Pressure Estimation Through Optimized Echo State Networks. 48-61 - Claudio Gallicchio, Alessio Micheli:
Reservoir Topology in Deep Echo State Networks. 62-75 - Hiromichi Suetani:
Multiple Pattern Generations and Chaotic Itinerant Dynamics in Reservoir Computing. 76-81 - Takanori Akiyama, Gouhei Tanaka:
Echo State Network with Adversarial Training. 82-88 - Pietro Verzelli, Cesare Alippi, Lorenzo Livi:
Hyper-spherical Reservoirs for Echo State Networks. 89-93 - Alexander Popov, Petia D. Koprinkova-Hristova, Kiril Simov, Petya Osenova:
Echo State vs. LSTM Networks for Word Sense Disambiguation. 94-109 - Rajkumar Ramamurthy, Robin Stenzel, Rafet Sifa, Anna Ladi, Christian Bauckhage:
Echo State Networks for Named Entity Recognition. 110-120 - Mantas Lukosevicius, Arnas Uselis:
Efficient Cross-Validation of Echo State Networks. 121-133
Workshop: Reservoir Computing - Physical Implementations
- Tomoyuki Kubota, Kohei Nakajima, Hirokazu Takahashi:
Echo State Property of Neuronal Cell Cultures. 137-148 - Jean-Pierre Locquet:
Overview on the PHRESCO Project: PHotonic REServoir COmputing. 149-155 - Piotr Antonik, Nicolas Marsal, Daniel Brunner, Damien Rontani:
Classification of Human Actions in Videos with a Large-Scale Photonic Reservoir Computer. 156-160 - Stijn Sackesyn, Chonghuai Ma, Andrew Katumba, Joni Dambre, Peter Bienstman:
A Power-Efficient Architecture for On-Chip Reservoir Computing. 161-164 - Jean Benoit Héroux, Naoki Kanazawa, Piotr Antonik:
Time Series Processing with VCSEL-Based Reservoir Computer. 165-169 - Miguel C. Soriano, Pau Massuti-Ballester, Jesús Yelo, Ingo Fischer:
Optoelectronic Reservoir Computing Using a Mixed Digital-Analog Hardware Implementation. 170-174 - Piotr Antonik, Nicolas Marsal, Daniel Brunner, Damien Rontani:
Comparison of Feature Extraction Techniques for Handwritten Digit Recognition with a Photonic Reservoir Computer. 175-179 - Jeremy Vatin, Damien Rontani, Marc Sciamanna:
Polarization Dynamics of VCSELs Improves Reservoir Computing Performance. 180-183 - Xavier Porte, Louis Andreoli, Maxime Jacquot, Laurent Larger, Daniel Brunner:
Reservoir-Size Dependent Learning in Analogue Neural Networks. 184-192 - Masanobu Inubushi, Susumu Goto:
Transferring Reservoir Computing: Formulation and Application to Fluid Physics. 193-199
Special Session: Artificial Intelligence in Medicine
- Wajid Mumtaz, Lukás Vareka, Roman Moucek:
Investigation of EEG-Based Graph-Theoretic Analysis for Automatic Diagnosis of Alcohol Use Disorder. 205-218 - Rongjun Ge, Guanyu Yang, Chenchu Xu, Jiulou Zhang, Yang Chen, Limin Luo, Cheng Feng, Heye Zhang, Shuo Li:
EchoQuan-Net: Direct Quantification of Echo Sequence for Left Ventricle Multidimensional Indices via Global-Local Learning, Geometric Adjustment and Multi-target Relation Learning. 219-230 - Ming Gao, Qifeng Xiao, Shaochun Wu, Kun Deng:
An Attention-Based ID-CNNs-CRF Model for Named Entity Recognition on Clinical Electronic Medical Records. 231-242 - Vadim Liventsev, Irina Fedulova, Dmitry V. Dylov:
Deep Text Prior: Weakly Supervised Learning for Assertion Classification. 243-257 - Hengjin Ke, Dan Chen, Lei Zhang, Xinhua Zhang, Xianzeng Liu, Xiaoli Li:
Inter-region Synchronization Analysis Based on Heterogeneous Matrix Similarity Measurement. 258-272 - Runze Wang, Yanan Guo, Wendao Wang, Yide Ma:
Bi-ResNet: Fully Automated Classification of Unregistered Contralateral Mammograms. 273-283 - Pouya Soltani Zarrin, Christian Wenger:
Pattern Recognition for COPD Diagnostics Using an Artificial Neural Network and Its Potential Integration on Hardware-Based Neuromorphic Platforms. 284-288 - Manish Mishra, Sabine Schmitt, Hans Zischka, Michael K. Strasser, Nassir Navab, Carsten Marr, Tingying Peng:
Quantifying Structural Heterogeneity of Healthy and Cancerous Mitochondria Using a Combined Segmentation and Classification USK-Net. 289-298 - Bogdan Kwolek, Michal Koziarski, Andrzej Bukala, Zbigniew Antosz, Boguslaw Olborski, Pawel Wasowicz, Jakub Swadzba, Boguslaw Cyganek:
Breast Cancer Classification on Histopathological Images Affected by Data Imbalance Using Active Learning and Deep Convolutional Neural Network. 299-312 - Konrad Kwolek, Henryk Liszka, Bogdan Kwolek, Artur Gadek:
Measuring the Angle of Hallux Valgus Using Segmentation of Bones on X-Ray Images. 313-325 - Junxiu Liu, Mingxing Li, Yuling Luo, Su Yang, Senhui Qiu:
Human Body Posture Recognition Using Wearable Devices. 326-337 - Zakhriya Alhassan, David Budgen, Ali Alessa, Riyad Alshammari, Tahani Daghstani, Noura Al Moubayed:
Collaborative Denoising Autoencoder for High Glycated Haemoglobin Prediction. 338-350
Special Session: Informed and Explainable Methods for Machine Learning
- Alex Sarishvili, Andreas Wirsen, Mats Jirstrand:
On Chow-Liu Forest Based Regularization of Deep Belief Networks. 353-364 - Christian Bauckhage, Rafet Sifa, Tiansi Dong:
Prototypes Within Minimum Enclosing Balls. 365-376 - Rohan Ghosh, Anupam K. Gupta:
Exploring Local Transformation Shared Weights in Convolutional Neural Networks. 377-390 - Raoul Heese, Michal Walczak, Lukas Morand, Dirk Helm, Michael Bortz:
The Good, the Bad and the Ugly: Augmenting a Black-Box Model with Expert Knowledge. 391-395 - Jader Abreu, Luis Fred, David L. Macêdo, Cleber Zanchettin:
Hierarchical Attentional Hybrid Neural Networks for Document Classification. 396-402 - Magnus Önnheim, Pontus Andersson, Emil Gustavsson, Mats Jirstrand:
Reinforcement Learning Informed by Optimal Control. 403-407 - Shogo Kitamura, Yuichi Nonaka:
Explainable Anomaly Detection via Feature-Based Localization. 408-419 - Rendani Mbuvha, Ilyes Boulkaibet, Tshilidzi Marwala:
Bayesian Automatic Relevance Determination for Feature Selection in Credit Default Modelling. 420-425 - Mohsin Munir, Shoaib Ahmed Siddiqui, Ferdinand Küsters, Dominique Mercier, Andreas Dengel, Sheraz Ahmed:
TSXplain: Demystification of DNN Decisions for Time-Series Using Natural Language and Statistical Features. 426-439 - Itay Mosafi, Eli (Omid) David, Nathan S. Netanyahu:
DeepMimic: Mentor-Student Unlabeled Data Based Training. 440-455 - Guglielmo Faggioli, Mirko Polato, Ivano Lauriola, Fabio Aiolli:
Evaluation of Tag Clusterings for User Profiling in Movie Recommendation. 456-468
Special Session: Deep Learning in Image Reconstruction
- Rafael Goncalves Pires, Daniel Felipe Silva Santos, Gustavo Botelho de Souza, Alexandre L. M. Levada, João Paulo Papa:
A Sparse Filtering-Based Approach for Non-blind Deep Image Denoising. 471-482 - Qingrong Cheng, Xiaodong Gu:
Hybrid Attention Driven Text-to-Image Synthesis via Generative Adversarial Networks. 483-495 - Sylwester Klocek, Lukasz Maziarka, Maciej Wolczyk, Jacek Tabor, Jakub Nowak, Marek Smieja:
Hypernetwork Functional Image Representation. 496-510 - H. V. L. C. Gamage, W. O. K. I. S. Wijesinghe, Indika Perera:
Instance-Based Segmentation for Boundary Detection of Neuropathic Ulcers Through Mask-RCNN. 511-522 - Antonio Jose Rodríguez-Sánchez, Tobias Dick:
Capsule Networks for Attention Under Occlusion. 523-534 - Bassel Zeno, Ilya Kalinovskiy, Yuri Matveev:
IP-GAN: Learning Identity and Pose Disentanglement in Generative Adversarial Networks. 535-547
Special Session: Machine Learning with Graphs: Algorithms and Applications
- Ivana Balazevic, Carl Allen, Timothy M. Hospedales:
Hypernetwork Knowledge Graph Embeddings. 553-565 - Junjie Huang, Huawei Shen, Liang Hou, Xueqi Cheng:
Signed Graph Attention Networks. 566-577 - Antoine J.-P. Tixier, Giannis Nikolentzos, Polykarpos Meladianos, Michalis Vazirgiannis:
Graph Classification with 2D Convolutional Neural Networks. 578-593 - Di Jin, Bingyi Li, Pengfei Jiao, Dongxiao He, Hongyu Shan:
Community Detection via Joint Graph Convolutional Network Embedding in Attribute Network. 594-606 - Adrian Horzyk, Krzysztof Goldon, Janusz A. Starzyk:
Temporal Coding of Neural Stimuli. 607-621 - Meng Cao, Xiying Ma, Ming Xu, Chongjun Wang:
Heterogeneous Information Network Embedding with Meta-path Based Graph Attention Networks. 622-634 - Feng Wei, Uyen Trang Nguyen, Hui Jiang:
Dual-FOFE-net Neural Models for Entity Linking with PageRank. 635-645 - Cleison Correia de Amorim, David L. Macêdo, Cleber Zanchettin:
Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition. 646-657 - Roman Schulte-Sasse, Stefan Budach, Denes Hnisz, Annalisa Marsico:
Graph Convolutional Networks Improve the Prediction of Cancer Driver Genes. 658-668 - Ananya Gupta, Elisabeth Welburn, Simon Watson, Hujun Yin:
CNN-Based Semantic Change Detection in Satellite Imagery. 669-684 - Marcin Orchel, Johan A. K. Suykens:
Axiomatic Kernels on Graphs for Support Vector Machines. 685-700 - Pedro H. C. Avelar, Henrique Lemos, Marcelo O. R. Prates, Luís da Cunha Lamb:
Multitask Learning on Graph Neural Networks: Learning Multiple Graph Centrality Measures with a Unified Network. 701-715
Special Session: BIGCHEM: Big Data and AI in Chemistry
- Amol Thakkar, Esben Jannik Bjerrum, Ola Engkvist, Jean-Louis Reymond:
Neural Network Guided Tree-Search Policies for Synthesis Planning. 721-724 - Mark McCormick, Alessandro E. P. Villa:
LSTM and 1-D Convolutional Neural Networks for Predictive Monitoring of the Anaerobic Digestion Process. 725-736 - Vibudh Agrawal, Francesco Gentile, Michael Hsing, Fuqiang Ban, Artem Cherkasov:
Progressive Docking - Deep Learning Based Approach for Accelerated Virtual Screening. 737-740 - Modest von Korff, Olivier Corminboeuf, John Gatfield, Sébastien Jeay, Isabelle Reymond, Thomas Sander:
Predictive Power of Time-Series Based Machine Learning Models for DMPK Measurements in Drug Discovery. 741-746 - Josep Arús-Pous, Simon Johansson, Oleksii Prykhodko, Esben Jannik Bjerrum, Christian Tyrchan, Jean-Louis Reymond, Hongming Chen, Ola Engkvist:
Improving Deep Generative Models with Randomized SMILES. 747-751 - Michael Withnall, Edvard Lindelöf, Ola Engkvist, Hongming Chen:
Attention and Edge Memory Convolution for Bioactivity Prediction. 752-757 - Hanoch Senderowitz, Abraham Yosipof, Omer Kaspi:
Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells. 758-763 - Dipan Ghosh, Igor V. Tetko, Bert Klebl, Peter Nussbaumer, Uwe Koch:
Analysis and Modelling of False Positives in GPCR Assays. 764-770 - Julio J. Valdés, Alain B. Tchagang:
Characterization of Quantum Derived Electronic Properties of Molecules: A Computational Intelligence Approach. 771-782 - Sebastian Reiter, Thomas Schnappinger, Regina de Vivie-Riedle:
Using an Autoencoder for Dimensionality Reduction in Quantum Dynamics. 783-787 - Jennifer Hemmerich, Ece Asilar, Gerhard F. Ecker:
Conformational Oversampling as Data Augmentation for Molecules. 788-792 - Alain B. Tchagang, Julio J. Valdés:
Prediction of the Atomization Energy of Molecules Using Coulomb Matrix and Atomic Composition in a Bayesian Regularized Neural Networks. 793-803 - Nelson R. C. Monteiro, Bernardete Ribeiro, Joel P. Arrais:
Deep Neural Network Architecture for Drug-Target Interaction Prediction. 804-809 - Lukasz Maziarka, Agnieszka Pocha, Jan Kaczmarczyk, Krzysztof Rataj, Michal Warchol:
Mol-CycleGAN - A Generative Model for Molecular Optimization. 810-816 - Pavel Karpov, Guillaume Godin, Igor V. Tetko:
A Transformer Model for Retrosynthesis. 817-830 - Igor V. Tetko, Pavel Karpov, Eric Bruno, Talia B. Kimber, Guillaume Godin:
Augmentation Is What You Need! 831-835
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