Description

Book Synopsis

Network structure and recurrent dynamics achieved by maximizing information transfer and minimizing maintenance costs of the network.- Outlier-Robust Range-Based Method for Estimating the Location and Velocity of a Moving Source Using Lagrange Programming Neural Network.- Spatial Analysis Techniques in Recognition and Localization of Mouse Neuronal Activity.- ScaleMixer: A Multi-Scale MLP-Mixer Model for Long-Term Time Series Forecasting.- Application of Pseudometric Functions in Clustering and a Novel Similarity Measure Based on Path Information Discrepancy.- USAM-Net: A U-Net based network for improved stereo correspondence and scene depth estimation using features from a pre-trained image segmentation network.- TaW-PeRCNN:Time-adaptive Weights Physics-encoded Recurrent Convolutional Neural Network for Solving Partial Differential Equations.- An Explainable Error Detection Approach for Machine Learning.- T-GET3D: A Generative Model of High-Quality 3D Textured Shapes Guided by Texts.- Conformal Adversarial Generative Ensemble.- Virtual Command Allocation: Enhancing Hexapod Robot Locomotion through Goal-Conditioned Reinforcement Learning.- Adaptive Retrieval-based Gradient Planning for Offine Multi-context Model-based Optimization.- RBHAR: Role-Based Heterogeneous Action Representation in Multi-Agent Reinforcement Learning.- Deep mixtures of variational autoencoders model for representation learning and clustering tasks.- TempoKGAT: A Novel Graph Attention Network Approach for Temporal Graph Analysis.- Direct Correlational Spike-Timing-Dependent Plasticity Learning Applied to Classification Tasks.- Wave-RVFL: A Randomized Neural Network Based on Wave Loss Function.- Dual Cross Fusion Deep-unfolding Transformer for Hyperspectral Image Reconstruction.- A weight averaging neural network for semi-supervised data stream learning.- obust Noise Tolerant Algorithm for Randomized Neural Network.- Tackling Periodic Distribution Shifts in Federated Learning with Half-cycle Knowledge Distillation.- Multi-Scale Attention Convolutional Network and Reinforcement Learning for Flexible Job Shop Scheduling.- Temporal State Prediction and Sequence Recovery for Multi-Agent Reinforcement Learning.- Data Augmentation with Variational Autoencoder for Imbalanced Dataset.- Performance Analysis of Quantum-Enhanced Kernel Classifiers Based on Feature Maps: A Case Study on EEG-BCI Data.- Certified Patch Defense via Dual Mask-Preservation Prediction.- Proximal Point Method for Online Saddle Point Problem.- Fast Preserving Local Distances and Topology in Auto-Encoders.- Neural Collapse Inspired Regularization for Deep Graph Neural Networks.

Neural Information Processing

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    A Paperback by Mufti Mahmud

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      Publisher: Springer
      Publication Date: Publication Date: 19/07/2025
      ISBN13: 9789819665785, 978-9819665785
      ISBN10:
      Also in:
      Pattern recognition

      Description

      Book Synopsis

      Network structure and recurrent dynamics achieved by maximizing information transfer and minimizing maintenance costs of the network.- Outlier-Robust Range-Based Method for Estimating the Location and Velocity of a Moving Source Using Lagrange Programming Neural Network.- Spatial Analysis Techniques in Recognition and Localization of Mouse Neuronal Activity.- ScaleMixer: A Multi-Scale MLP-Mixer Model for Long-Term Time Series Forecasting.- Application of Pseudometric Functions in Clustering and a Novel Similarity Measure Based on Path Information Discrepancy.- USAM-Net: A U-Net based network for improved stereo correspondence and scene depth estimation using features from a pre-trained image segmentation network.- TaW-PeRCNN:Time-adaptive Weights Physics-encoded Recurrent Convolutional Neural Network for Solving Partial Differential Equations.- An Explainable Error Detection Approach for Machine Learning.- T-GET3D: A Generative Model of High-Quality 3D Textured Shapes Guided by Texts.- Conformal Adversarial Generative Ensemble.- Virtual Command Allocation: Enhancing Hexapod Robot Locomotion through Goal-Conditioned Reinforcement Learning.- Adaptive Retrieval-based Gradient Planning for Offine Multi-context Model-based Optimization.- RBHAR: Role-Based Heterogeneous Action Representation in Multi-Agent Reinforcement Learning.- Deep mixtures of variational autoencoders model for representation learning and clustering tasks.- TempoKGAT: A Novel Graph Attention Network Approach for Temporal Graph Analysis.- Direct Correlational Spike-Timing-Dependent Plasticity Learning Applied to Classification Tasks.- Wave-RVFL: A Randomized Neural Network Based on Wave Loss Function.- Dual Cross Fusion Deep-unfolding Transformer for Hyperspectral Image Reconstruction.- A weight averaging neural network for semi-supervised data stream learning.- obust Noise Tolerant Algorithm for Randomized Neural Network.- Tackling Periodic Distribution Shifts in Federated Learning with Half-cycle Knowledge Distillation.- Multi-Scale Attention Convolutional Network and Reinforcement Learning for Flexible Job Shop Scheduling.- Temporal State Prediction and Sequence Recovery for Multi-Agent Reinforcement Learning.- Data Augmentation with Variational Autoencoder for Imbalanced Dataset.- Performance Analysis of Quantum-Enhanced Kernel Classifiers Based on Feature Maps: A Case Study on EEG-BCI Data.- Certified Patch Defense via Dual Mask-Preservation Prediction.- Proximal Point Method for Online Saddle Point Problem.- Fast Preserving Local Distances and Topology in Auto-Encoders.- Neural Collapse Inspired Regularization for Deep Graph Neural Networks.

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