The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023.  The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields. 

Table of Contents:
Theory and Algorithms.- Single Feedback Based Kernel Generalized Maximum Correntropy Adaptive Filtering Algorithm.- Application of Deep learning methods in the Diagnosis of Coronary Heart Disease based on Electronic Health Record.- Learning Adaptable Risk-Sensitive Policies to Coordinate in Multi-Agent General-Sum Games.- Traffic Data Recovery and Outlier Detection based on Non-Negative Matrix Factorization and Truncated-Quadratic Loss Function.- ADEQ: Adaptive Diversity Enhancement for Zero-shot Quantization.- ASTPSI: Allocating Spare Time and Planning Speed Interval for Intelligent Train Control of Sparse Reward.- Amortized variational inference via Nos\'e-Hoover Thermostat Hamiltonian Monte Carlo.- AM-RRT*: An Automatic Robot Motion Planning Algorithm based on RRT.- MS3DAAM: Multi-scale 3-D Analytic Attention Module for Convolutional Neural Networks.- Nonlinear Multiple-delay Feedback Based Kernel Least Mean Square Algorithm.- AGGDN: A Continuous Stochastic Predictive Model for Monitoring Sporadic Time Series on Graphs.- Attribution Guided Layerwise Knowledge Amalgamation from Graph Neural Networks.- Distributed Neurodynamic Approach for Optimal Allocation with Separable Resource Losses.- Multimodal Isotropic Neural Architecture with Patch Embedding.- Determination of local and global decision weights based on fuzzy modeling.- Binary Mother Tree Optimization Algorithm for 0/1 Knapsack Problem.- Distributed State Estimation for Multi-Agent Systems Under Consensus Control.- Integrated Design of Fully Distributed Adaptive State Estimation and Consensus Control for Multi-Agent Systems.- Computer Simulations of Applying Zhang Inequation Equivalency and Solver of Neurodynamics to Redundant Manipulators at Acceleration Level.- High-order control barrier function based robust collision avoidance formation tracking of constrained multi-agent systems.- Decision Support System based on MLP: Formula One (F1) Grand Prix Study Case.- Theoretical Analysis of Gradient-ZhangNeural Network for Time-Varying Equations and Improved Method for Linear Equations.- EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices.- Mastering Complex Coordination through Attention-based Dynamic Graph.- SORA: Improving Multi-agent Cooperation with a Soft Role Assignment Mechanism.- Outer Synchronization for Multi-Derivative Coupled Complex Networks with and without External Disturbance.- A Distributed Projection-based Algorithm with Local Estimators for Optimal Formation of Multi-robot System.- A Stochastic Gradient-based Projection Algorithm for Distributed Constrained Optimization.- FalconNet: Factorization for the Light-weight ConvNets.- An Interactive Evolutionary Algorithm for Ceramic Formula Design.- Using Less But Important Information for Feature Distillation.- Efficient Mobile Robot Navigation Based on Federated Learning and Three-way Decisions.- GCM-FL: A Novel Granular Computing Model in Federated Learning for Fault Diagnosis.- Adaptive loadfrequency control and optimization based on TD3 algorithm and linear active disturbance rejection control.- Theory-guided Convolutional Neural Network with an Enhanced Water Flow Optimizer.- An End-to-End Dense Connected Heterogeneous Graph Convolutional Neural Network.- Actor-Critic with variable time discretization via sustained actions.- Scalable Bayesian Tensor Ring Factorization for Multiway Data Analysis.- Predefined-Time Event-Triggered Consensus for Nonlinear Multi-Agent Systems with Uncertain Parameter.- Cascaded fuzzy PID control for quadrotor UAVs based on RBF neural networks.- Generalizing Graph Network Models for the Traveling Salesman Problem with Lin-Kernighan-Helsgaun Heuristics.- Communication-Efficient Distributed Minimax Optimization via Markov Compression.- Multi-Level Augmentation Boosts Hybrid CNN-Transformer Model for Semi-Supervised Cardiac MRI Segmentation.- Wasserstein Diversity-Enriched Regularizer for Hierarchical Reinforcement Learning.- An Adaptive Detector for Few Shot Object Detection.