Artificial Neural Networks and Machine Learning - Icann 2019: Theoretical Neural Computation

Bidirectional associative memory with block coding: A comparison of iterative retrieval methods.- Stability analysis of a generalised class of BAM neural networks with mixed delays.- Dissipativity Analysis of a Class of Competitive Neural Networks with Proportional Delays.- A Nonlinear Fokker-Planck Description of Continuous Neural Network Dynamics.- Multi-modal associative storage and retrieval using Hopfield auto-associative memory network.- Chaotic Complex-Valued Associative Memory with Adaptive Scaling Factor Independent of Multi-Values.- A Comparative Analysis of Preprocessing Methods for Single-Trial Event Related Potential Detection.- Sleep State Analysis using Calcium Imaging Data by Non-negative Matrix Factorization.- Detection of directional information flow induced by TMS based on symbolic transfer entropy.- Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network.- Distinguishing Violinists and Pianists based on their Brain Signals.- Research on Image-to-Image Translation with Capsule Network.- Multi-View Capsule Network.- Advanced Capsule Networks via Context Awareness.- DDRM-CapsNet: Capsule Network based on Deep Dynamic Routing Mechanism for complex data.- Squeezed Very Deep Convolutional Neural Networks for Text Classification.- NeuroPower: Designing Energy Efficient Convolutional Neural Network Architecture for Embedded Systems.- Swap kernel regression.- Model-Agnostic Explanations for Decisions using Minimal Patterns.- NARPCA: Neural Accumulate-Retract PCA for Low-latency High-throughput Processing on Datastreams.- An Evaluation of Various Regression Models for the Prediction of Two-Terminal Network Reliability.- Capsule Generative Models.- Evaluating CNNs on the Gestalt Principle of Closure.- Recovering Localized Adversarial Attacks.- On the Interpretation of Recurrent Neural Networks as Finite State Machines.- Neural field model for measuring and reproducing time intervals.- Widely Linear Complex-valued Autoencoder: Dealing with Noncircularity in Generative-Discriminative Models.- NatCSNN: A Convolutional Spiking Neural Network for recognition of objects extracted from natural images.- Deep Semantic Asymmetric Hashing.- A Neural Network for Semi-Supervised Learning on Manifolds.- Counting with Analog Neurons.- On the Bounds of Function Approximations.- Probabilistic Bounds for Approximation by Neural Networks.- Tree Memory Networks for Sequence Processing.- On Deep Set Learning and the Choice of Aggregations.- Hilbert Vector Convolutional Neural Network: 2D Neural Network on 1D Data.- The Same Size Dilated Attention Network for Keypoint Detection.- Gradient-Based Learning of Compositional Dynamics with Modular RNNs.- Transfer Learning with Sparse Associative Memories.- Linear Memory Networks.- A Multi-Armed Bandit Algorithm Available in Stationary or Non-Stationary Environments Using Self-Organizing Maps.- Cooperation and Coordination Regimes by Deep Q-Learning in Multi-agent Task Executions.- Boosting Reinforcement Learning with Unsupervised Feature Extraction.- A multi-objective Reinforcement Learning algorithm for JSSP.- A Reinforcement Learning Approach for Sequential Spatial Transformer Networks.- Deep Recurrent Policy Networks for Planning under Partial Observability.- Mixed-Reality Deep Reinforcement Learning for a Reach-to-grasp Task.- FMNet: Multi-Agent Cooperation by Communicating with Featured Message Network.- Inferring Event-Predictive Goal-Directed Object Manipulations in REPRISE.- On Unsupervised Learning of Traversal Cost and Terrain Types Identification using Self-Organizing Maps.- Scaffolding Haptic Attention with Controller Gating.- Benchmarking Incremental Regressors in Traversal Cost Assessment.- CPG driven RBF Network Control with Reinforcement Learning for Gait Optimization of a Dung Beetle-like Robot.- Training Delays in Spiking Neural Networks.- An Izhikevich Model Neuron MOS Circuit for Low Voltage Operation.- U