IJCNN —— CCF C会议 投稿分类

Primary Secondary Primary Secondary
Applications of Neural Networks
Special Sessions

AI for critical infrastructures

Addressing challenges in Nuclear Fusion with Machine Learning

Audio analysis and synthesis

Advances in Compression Techniques for Scalable and Efficient Deep Neural Networks

Autonomous vehicles and intelligent transportation

Advances in Deep Learning for Biomedical Data Analysis

Bioinformatics

Advances in Time-Series Data: Novel Theories, Methods, and Applications

Biomedical engineering

Advancing Physics-Informed Neural Networks: Bridging Scientific Principles and Machine Learning for Complex Systems

Digital twins

Advancing Structural Engineering with Neural Networks and AI: Design, Assessment, and Optimization

Financial engineering applications

AI for Social Good

Healthcare and life sciences

AI-Driven Revolution in Healthcare: Exploring Foundation Models and Their Applications

Image and video processing

AI, Law and Regulation

Manufacturing and industrial applications

AICS: Artificial Intelligence for Complex Systems

Neural models for computer graphics

Application of Explainable Neural Network Models in Processing and Analysis of Neuronal Data

Neural networks for communications

Artificial Intelligence and Machine Learning Innovations: Showcasing Funded European Projects

Other applications

Artificial Intelligence for Neural Engineering: Innovations, Applications and Future Directions

Power system applications

Artificial Intelligence in Healthcare: Leveraging Transformer Models

Privacy and security

Artificial Intelligence in Software Quality and Evolution

Robotics

Bayesian Methods for Inference and Learning

Smart grid applications

Bayesian Neural Networks: The Interplay between Bayes’ Theorem and Neural Networks

Social media networks

Biologically Inspired Neural Networks and Learning Systems for Robotics and Mechatronics

Speech enhancement and recognition

Collaborative Learning of Trustworthy Computational Intelligence Systems (CLOTHES 2025)

Time series analysis

Complex- and Hypercomplex-Valued Neural Networks
Computational Neurosciences

Computational Intelligence and Software Engineering

Brain imaging

Computational Intelligence in Transactive Energy Management and Smart Energy Network (CITESEN 2025)

Brain-inspired models

Cross-Domain Innovations in Neural Network Methods and Applications

Brain-machine interfaces

Cybersecurity in Complex Environments (CCE)

Cognitive models

Data Science: Multidisciplinary Perspectives to Tame the Data Revolution

Collective and swarm intelligence

Data-Efficient Vision Transformers: Challenges & Applications

Knowledge representation and reasoning

Deep Edge Intelligence

Nervous system modeling

Deep Learning for Digital Twin Models (DLDTM)

Neuroengineering

Deep Learning in Computational Biology and Biomedicine: from Biomedical Data to Drug Discovery

Neuromorphic systems

Deep Neural Architecture Generation for Generative Models and Adversarial Learning for Image/Video/Audio/Text Processing

Neurophysiological data analysis

Deep Vision in Space

Neurosymbolic AI

Design and Theory of Deep Graph Learning

Other topics in computational neuroscience

Digital Twinning in Smart Applications
Cross-Disciplinary topics

Distributed Learning and Intelligent Systems: Advancing Privacy and Scalability for IoT and Edge Networks

AI ethics and regulation

Domain Adaptation for Complex Situations: Theories, Algorithms and Applications

AI for Education

Ethical, Legal and Social Implications of Computational Intelligence

Artificial immune systems

Evolutionary Computation in Wireless Communications

Climate sciences

Explainable AI in Neural Networks: Advances, Challenges, and Applications

Complex system modeling

Explainable Artificial Intelligence in Bioengineering (EAIB)

Computation in tissues and cells

Explainable Artificial Intelligence Techniques for Open Government

Computational biology

Explainable Deep Neural Networks for Responsible AI: Post-Hoc and Self-Explaining Approaches (DeepXplain 2025)

Materials modeling and design

Exploring Advanced Techniques and Applications in AutoML

Mathematics of neural networks

Foundation Models in Medicine (FMM)

Molecular and DNA computation

Generative AI in Privacy and Security: Challenges and Perspectives

Neural networks for scientific discovery

GPAIT 2: General Purpose Artificial Intelligence Technologies and Trustworthiness

Other cross-disciplinary topics

Graph-based solutions for Artificial Intelligence

Physics-informed neural networks

Graph/Hypergraph Neural Networks for Structural Analysis
Machine Learning

Human-Centered Artificial Intelligence (HCAI)

Bayesian learning and probabilistic models

Human-like Intelligence

Causal machine learning

Hyperdimensional Computing and Vector Symbolic Architectures for Neural Networks and Artificial Intelligence

Continual learning

Integrated Machine Learning and Wireless Communication (IMAC)

Data analytics and visualization

Intelligent Vehicles and Transportation Systems (IVTS)

Deep learning theory

Leveraging Foundation Models for Efficiently Developing Generative Models

Feature selection and extraction

Leveraging Large Language Models for Healthcare Innovation

Information-theoretic learning

LLMs in Motion: Transformative Advances in LLMs for Autonomous Navigation and Decision-Making at the Edge

Interpretable and explainable AI

Machine Learning and Deep Learning Methods applied to Vision and Robotics (MLDLMVR)

Optimization algorithms for neural networks

Machine Learning for Optimisation

Other topics in machine learning

Machine Learning in Complex Energy Systems and Future Sustainability

Reinforcement learning

Multimodal Deep Learning in Applications

Self-supervised learning

Neural Architecture Search's Theory, Algorithm and Application

Supervised learning

Neural methods for IR and RecSys

Support vector machines and kernel methods

Neural networks for nondestructive evaluation and structural health monitoring

Sustainable AI

NeuroCAS: Neuromorphic Computing for Intelligent Autonomous Systems

Topological deep learning

Privacy-Preserving Human Pose Estimation

Trustworthy and reliable machine learning

Privacy-Preserving Machine and Deep Learning

Unsupervised learning and clustering

Quantum Machine Learning Algorithms and Applications
Neural Network Models

Randomization Based Deep and Shallow Learning Methods and Applications to Healthcare Domain

Associative memory and attractor networks

Recent Trends in Communication and Data Analyzing Techniques for IoT (RTCDATI)

Convolutional neural networks

Reservoir computing in the deep learning era: theory, models, applications, and hardware implementations

Dynamic neural networks

Responsible Foundation Models in the Wild

Efficient and tiny neural networks

SAFE machine learning

Feedforward neural networks

Self-organizing Clustering for Continual Learning and its Applications

Generative models

Sustainable AI for Internet-of-Things (IoT) networks

Graph neural networks

Synergies between Quantum Computing and Machine Learning

Large-scale neural networks

Systems-Theoretic Approaches to Learning II: Applications to System Identification, State Estimation and Control

LLM-based networks

Tiny Machine Learning

Mixture of experts

Towards Robust Federated Learning: Addressing Data and Device Heterogeneity

Modular neural networks

Trustworthy and Explainable Federated Learning: Towards Security and Privacy Future

Multimodal neural networks

Trustworthy and Reliable Artificial Intelligence Applications in Healthcare Decision-Making

Other neural network models

Special Track - Human-AI interaction in creative arts and sciences

Quantum neural networks

Radial basis function networks

Recurrent neural networks

Reservoir and echo-state networks

Self-organizing maps

Spiking neural networks

State-space neural models

Transformers and attention-based networks