Artificial Neural Networks and Machine Learning - ICANN 2019: Workshop and Special Sessions

SynchronizationAnalysis based on Heterogeneous Matrix Similarity Measurement.- Bi-ResNet: Fully automated classification of unregistered contralateral mammograms.- Pattern Recognition for COPD Diagnostics Using an Artificial Neural Network and Its Potential Integration on Hardware-based Neuromorphic Platforms.- Quantifying Structural Heterogeneity of Healthy and Cancerous Mitochondria using a Combined Segmentation and Classification USK-Net.- Breast Cancer Classification on Histopathological Images Affected by Data Imbalance Using Active Learning and Deep Convolutional Neural Network.- Measuring the Angle of Hallux Valgus Using Segmentation of Bones on X-ray Images.- Human Body Posture Recognition Using Wearable Devices.- Collaborative Denoising Autoencoder for High Glycated Haemoglobin Prediction.- On Chow-Liu forest based regularization of deep belief networks.- Prototypes within Minimum Enclosing Balls.- Exploring Local Transformation Shared Weights in Convolutional Neural Networks.- The Good, theBad and the Ugly: augmenting a black-box model with expert knowledge.- Hierarchical Attentional Hybrid Neural Networks for Document Classification.- Reinforcement learning informed by optimal control.- Explainable Anomaly Detection via Feature-Based Localization.- Bayesian Automatic Relevance Determination for Feature selection in Credit Default Modelling.- TSXplain: Demystification of DNN Decisions for Time-Series using Natural Language and Statistical Features.- DeepMimic: Mentor-Student Unlabeled Data Based Training.- Evaluation of tag clusterings for user profiling in movie recommendation.- A Sparse Filtering-based Approach for Non-Blind Deep Image Denoising.- Hybrid Attention Driven Text-to-Image Synthesis via Generative Adversarial Networks.- Hypernetwork functional image representation.- Instance-based Segmentation for Boundary Detection of Neuropathic Ulcers through Mask-RCNN.- Capsule Networks for attention under occlusion.- IP-GAN: Learning Identity and Pose Disentanglementin Generative Adversarial Networks.- Hypernetwork Knowledge Graph Embeddings.- Signed Graph Attention Networks.- Graph Classification with 2D Convolutional Neural Networks.- Community Detection via Joint Graph Convolutional Network Embedding in Attribute Network.- Temporal Coding of Neural Stimuli.- Heterogeneous Information Network Embedding with Meta-path-based Graph Attention Networks.- Dual-FOFE-net Neural Models for Entity Linking with PageRank.- Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition.- Graph Convolutional Networks Improve the Prediction of Cancer Driver Genes.- CNN-Based Semantic Change Detection in Satellite Imagery.- Axiomatic Kernels on Graphs for Support Vector Machines.- Multitask Learning on Graph Neural Networks: Learning Multiple Graph Centrality Measures with a Unified Network.- Neural Network Guided Tree-Search Policies for Synthesis Planning .- LSTM and 1-D Convolutional Neural Networks for predictive monitoring of the anaerobic digestion process.- Progressive Docking - a Deep Learning Based Approach for Accelerated Virtual Screening.- Predictive Power of Time-series Based Machine Learning Models for DMPK Measurements in Drug Discovery.- Improving Deep Generative Models with Randomized SMILES.- Attention and Edge Memory Convolution for Bioactivity Prediction.- Application of materials informatics tools to the analysis of combinatorial libraries of all metal-oxides photovoltaic cells.- Analysis and Modelling of False Positives in GPCR Assays.- Characterization of Quantum Derived Electronic Properties of Molecules: A Computational Intelligence Approach.- Using an Autoencoder for Dimensionality Reduction in Quantum Dynamics.- Conformational Oversampling as Data Augmentation for Molecules.- Prediction of the Atomization Energy of Molecules Using Coulomb Matrix and Atomic Composition in a Bayesian Regularized Neural Networks.- Deep Neural Network Architecture for Drug-Target Interaction Prediction.- Mol-CycleGAN - a generative model for molecular optimization.- A TRANSFORMER MODEL FOR RETROSYNTHESIS.- Augmentation is What You Need!.- Diversify Libraries Using Generative Topographic Mapping.- Detection of Frequent-Hitters across various HTS Technologies.- Message Passing Neural Networks scoring functions for structure-based drug discovery.