Artificial Neural Networks and Machine Learning - ICANN 2021

Generative neural networks.- Binding and Perspective Taking as Inference in a Generative Neural Network Model .- Advances in Password Recovery using Generative Deep Learning Techniques.- o 0886 - Dilated Residual Aggregation Network for Text-guided Image Manipulation.- Denoising AutoEncoder based Delete and Generate Approach for Text Style Transfer.- GUIS2Code: A Computer Vision Tool to Generate Code Automatically from Graphical User Interface Sketches.- Generating Math Word Problems from Equations with Topic Consistency Maintaining and Commonsense Enforcement.- Generative properties of Universal Bidirectional Activation-based Learning.- Graph neural networks I .- Joint Graph Contextualized Network for Sequential Recommendation.- Relevance-Aware Q-matrix Calibration for Knowledge Tracing.- LGACN: A Light Graph Adaptive Convolution Network for Collaborative Filtering.- HawkEye: Cross-Platform Malware Detection with Representation Learning on Graphs.- An Empirical Study of the Expressiveness of Graph Kernels and Graph Neural Networks.- Multi-resolution Graph Neural Networks for PDE approximation.- Link Prediction on Knowledge Graph by Rotation Embedding on the Hyperplane in the Complex Vector Space.- Graph neural networks II.- Contextualise Entities and Relations: An Interaction Method for Knowledge Graph Completion.- Civil Unrest Event Forecasting Using Graphical and Sequential Neural Networks.- Parameterized Hypercomplex Graph Neural Networks for Graph Classification.- Feature Interaction Based Graph Convolutional Networks For Image-text Retrieval.- Generalizing Message Passing Neural Networks to Heterophily using Position Information.- Local and Non-local Context Graph Convolutional Networks for Skeleton-based Action Recognition.-STGATP: A Spatio-temporal Graph Attention Network for Long-term Traffic Prediction.- Hierarchical and ensemble models.- Integrating N-Gram Features into Pre-Trained Model: A Novel Ensemble Model for Multi-Target Stance Detection.- Hierarchical Ensemble for Multi-view Clustering.- Structure-Aware Multi-Scale Hierarchical Graph Convolutional Network for Skeleton Action Recognition.- Learning Hierarchical Reasoning for Text-based Visual Question Answering.- Hierarchical Deep Gaussian Processes Latent Variable Model via Expectation Propagation.- Adaptive Consensus-Based Ensemble for Improved Deep Learning Inference Cost.- Human pose estimation.- Multi-Branch Network for Small Human Pose Estimation.- PNO: Personalized Network Optimization for Human Pose and Shape Reconstruction.- JointPose: Jointly Optimizing Evolutionary Data Augmentation and Prediction Neural Network for 3D Human Pose Estimation.- DeepRehab: Real Time Pose Estimation on the Edge for Knee Injury Rehabilitation.- Image processing.- Subspace constraint for Single Image Super-Resolution.- Towards Fine-Grained Control over Latent Space for Unpaired Image-to-Image Translation.- FMSNet: Underwater Image Restoration by Learning from a Synthesized Dataset.- Towards Measuring Bias in Image Classification.- Towards Image Retrieval with Noisy Labels via Non-deterministic Features.- Image segmentation.- Improving Visual Question Answering by Semantic Segmentation.- Weakly Supervised Semantic Segmentation with Patch-Based Metric Learning Enhancement.- ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation.- Depth Mapping Hybrid Deep Learning Method for Optic Disc and Cup Segmentation on Stereoscopic Ocular Fundus.- RATS: Robust Automated Tracking and Segmentation of Similar Instances.- Knowledge distillation.- Data Diversification Revisited: Why Does It Work?.- A Generalized Meta-Loss Function for Distillation Based Learning Using Privileged Information for Classification and Regression.- Empirical Study of Data-Free Iterative Knowledge Distillation.- Adversarial Variational Knowledge Distillation.- Extract then Distill: Efficient and Effective Task-Agnostic BERT Distillation.- Medical image processing.- Semi-supervised Learning based Right Ventricle Segmentation Using Deep Convolutional Boltzmann Machine Shape Model.- Improved U-Net for Plaque Segmentation of Intracoronary Optical Coherence Tomography Images.- Approximated Masked Global Context Network for Skin Lesion Segmentation.- DSNet: Dynamic Selection Network for Biomedical Image Segmentation.- Computational Approach to Identifying Contrast-Driven Retinal Ganglion Cells.- Radiological Identification of Hip Joint Centers from X-ray Images Using Fast Deep Stacked Network and Dynamic Registration Graph.- A Two-Branch Neural Network for Non-Small-Cell Lung Cancer Classification and Segmentation.- Uncertainty Quantification and Estimation in Medical Image Classification.- Labeling Chest X-Ray Reports Using Deep Learning.