IJCNN 2021 Program Time zone UTC + 1 Welcome: Welcome and Opening Address Session S1: Artificial Intelligence and Security (AISE)
Session S2: Healthcare Analytics: Improving Healthcare outcomes using Multimedia Data Analytics
Session S3: Adversarial Machine Learning and Cyber Security
Session S4: Representation Learning for Audio, Speech, and Music Processing
Session S24: Data Analytics and Computation Intelligence for Internet of Everything
Session S6: Randomization-Based Deep and Shallow Learning Algorithms
Session S7: Online Intelligence And Trust Computation In Large-Scale Dynamic Networks
Session S10: Evolving Machine Learning and Deep Learning Models for Computer Vision
Plenary Poster Session I1: Neural Network Models
Plenary Poster Session I2: Neural Network Models
Plenary Talk PleSun1: Marios M. Polycarpou Plenary Talk PleSun2: Active Inference, Professor Karl J. Friston Session S11: AutoML and its applications in Deep Learning
Session S2a: Healthcare Analytics: Improving Healthcare outcomes using Multimedia Data Analytics
Session S3a: Adversarial Machine Learning and Cyber Security
Session S4a: Representation Learning for Audio, Speech, and Music Processing
Session S25: Feature Extraction and Learning on Image and Text Data
Session S6a: Randomization-Based Deep and Shallow Learning Algorithms
Session S7a: Online Intelligence And Trust Computation In Large-Scale Dynamic Networks
Session S12: Deep Learning for Financial Data Analysis
Plenary Poster Session I3: Deep neural networks
Plenary Poster Session I4: Deep neural networks
Session S13: Deep Neural Networks-Based Recommender System
Session S14: Reservoir Computing: Advances in Models, Applications, and Implementations
Session S3b: Adversarial Machine Learning and Cyber Security
Session S15: Advanced Algorithms of Machine Learning and Artificial Intelligence Applied for Biomedical Data Processing
Session S25a: Feature Extraction and Learning on Image and Text Data
Session S18: Special Session on Federated Learning and Cooperative Neural Networks (CoNN)
Session S19: Machine Learning in Noisy Intermediate-Scale Quantum devices
Session S21: Learning from Imbalanced and Difficult Data
Plenary Poster Session I5: Deep neural networks
Plenary Poster Session I6: Deep neural networks
Session S5c: Machine Learning and Deep Learning Methods applied to Vision and Robotics (MLDLMVR)
Session S15a: Advanced Algorithms of Machine Learning and Artificial Intelligence Applied for Biomedical Data Processing
Session S18a: Special Session on Federated Learning and Cooperative Neural Networks (CoNN)
Session S21a: Learning from Imbalanced and Difficult Data
Session S22: Deep and Generative Adversarial Learning
Session S23: Current Trend of Machine Learning in Computer Vision
Session S26: Metrology, Verification, and Explanation of Data-Driven AI Systems and Neural Networks
Session S29: Bayesian Neural Networks & AutoML applications
Plenary Poster Session I7: Deep neural networks
Plenary Poster Session I8: Other topics and Supervised Learning
Session S5: Machine Learning and Deep Learning Methods applied to Vision and Robotics (MLDLMVR)
Session L1: Feedforward neural networks
Session L2: Feedforward neural networks
Session L3: Feedforward neural networks
Session L4: Recurrent Neural Networks
Session L5: Recurrent Neural Networks
Session S26a: Metrology, Verification, and Explanation of Data-Driven AI Systems and Neural Networks
Session L6: Neural Networks Models
Plenary Poster Session I9: Machine Learning and Deep Learning
Plenary Poster Session I10: Machine Learning and Deep Learning
Plenary Talk PleMon: What neuroimaging can tell about human brain function, Riitta Salmelin Session S5a: Machine Learning and Deep Learning Methods applied to Vision and Robotics (MLDLMVR)
Session L7: Spiking Neural Networks
Session L8: Spiking Neural Networks
Session L9: Spiking Neural Networks and Other models
Session L10: Deep neural networks
Session L11: Deep neural networks
Session L12: Deep neural networks
Session L13: Deep neural networks
Plenary Poster Session I11: Machine Learning and Deep Learning
Plenary Poster Session I12: Machine Learning and Deep Learning
Plenary Talk PleTue1: Fascinating World of Recurrent Networks: A Personal View, Peter Tino Plenary Talk PleTue2: Zongben XuXi’an Session S5b: Machine Learning and Deep Learning Methods applied to Vision and Robotics (MLDLMVR)
Session L14: Deep neural networks
Session L15: Deep neural networks
Session L16: Deep neural networks
Session L17: Deep neural networks
Session L18: Deep neural networks
Session L19: Deep neural networks
Session L20: Deep neural networks
Plenary Poster Session I13: Machine Learning and Deep Learning
Plenary Poster Session I14: Machine Learning and Deep Learning
Session S24a: Data Analytics and Computation Intelligence
Session L21: Deep neural networks
Session L22: Deep neural networks
Session L23: Other topics in ANN
Session L24: Other topics in ANN
Session L25: Supervised Learning
Session L26: Supervised Learning
Session L27: Unsupervised learning and clustering
Plenary Poster Session I15: Machine Learning and Deep Learning
Plenary Poster Session I16: Machine Learning and Deep Learning
Session L28: Unsupervised learning and clustering
Session L29: Other topics Machine Learning
Session L30: Other topics Machine Learning
Session L31: Other topics Machine Learning
Session L32: Reinforcement learning and adaptive dynamic programming
Session L33: Reinforcement learning and adaptive dynamic programming
Session L34: Reinforcement learning and adaptive dynamic programming
Session L35: Reinforcement learning and adaptive dynamic programming
Plenary Poster Session I17: Neural Models and Cognition
Plenary Poster Session I18: Neural Models and Cognition, Neurodynamics
Session L36: Semi-supervised learning
Session L37: Semi-supervised learning
Session L38: Deep Learning
Session L39: Deep Learning
Session L40: Deep Learning
Session L41: Deep Learning
Session L42: Deep Learning
Session L43: Deep Learning
Plenary Poster Session I19: Bio-inspired systems and application
Plenary Poster Session I20: Bio-inspired systems and application
Session L44: Deep Learning
Session L45: Deep Learning
Session L46: Deep Learning
Session L47: Online learning
Session L48: Online learning and other Neurodynamics
Session L49: Probabilistic methods and Gaussian processes
Session L50: Mixture models, ensemble learning, and other meta-learning or committee algorithms
Session L51: Computational Neuroscience and Bio-inspired systems
Plenary Poster Session I21: Bio-inspired systems and application
Plenary Poster Session I22: Bio-inspired systems and application
Plenary Talk PleWed: Dietmar Plenz Session L52: Perception and Cognition
Session L53: NN models and Neuroengineering
Session L54: Neuroengineering
Session L55: Bio-inspired systems
Session L56: Applications of deep networks
Session L57: Applications of deep networks
Session L58: Applications of deep networks
Session L59: Applications of deep networks
Plenary Poster Session I23: Bio-inspired systems and application
Plenary Poster Session I24: Bio-inspired systems and application
Plenary Talk PleThu1: Transfer Learning and Knowledge Transfer Between Humans and Machines with Brain-Inspired Spiking Neural Networks for Adaptable and Explainable AI, Nikola Kasabov Plenary Talk PleThu2: Awards & Closing Address Session L60: Applications of deep networks
Session L61: Applications of deep networks
Session L62: Applications of deep networks
Session L63: Applications of deep networks
Session L64: Big Data & Pattern recognition
Session L65: Pattern Recognition
Session L66: Pattern and Speech Recognition
Session L67: Speech Recognition & Robotics
Plenary Poster Session I25: ANN Applications and Models
Plenary Poster Session I26: ANN Applications and Models
Session L68: Robotics & NN approaches to Optimization
Session L69: Optimisation and Signal Processing
Session L70: Signal processing, image processing, and multi-media
Session L71: Signal processing, image processing, and multi-media
Session L72: Signal processing, image processing, and multi-media
Session L73: Temporal data analysis, prediction, and forecasting; time series analysis
Session L74: Temporal data analysis, prediction, and forecasting; time series analysis
Session L75: Temporal data analysis, prediction, and forecasting; time series analysis
Plenary Poster Session I27: Deep Learning and Applications
Plenary Poster Session I28: Deep Learning and Applications
Session L76: Communications and computer networks
Session L77: Data mining and knowledge discovery
Session L78: Data mining and knowledge discovery
Session L79: Data mining and knowledge discovery
Session L80: Intelligent Systems and Applications
Session L81: Intelligent Systems and Applications
Session L82: Intelligent Systems
Session L83: Intelligent Systems
Plenary Poster Session I29: Deep Learning and Applications
Plenary Poster Session I30: Deep Learning and Applications
Tutorial T1: Reservoir Computing: Randomized Recurrent Neural Networks Tutorial T2: Machine Learning for Brain-Computer Interfaces Tutorial T3: Deep Learning for Graphs Tutorial T5: Accelerating Deep Learning Computation Plenary Poster Session I31: Deep Learning and Applications
Tutorial T4: Design Solutions using Bayesian Optimization Tutorial T6: Randomization Based Deep and Shallow Learning Methods for Classification and Forecasting Tutorial T7: Intelligent System Research‚ AI Ethical Challenges and Opportunities Tutorial T8: Deep learning applied to the viral genome classification Session L84: Deep Learning and Applications
Workshop W1: Deep Learning in Unconventional Neuromorphic Hardware Workshop W2: Advances on Artificial Intelligence for the Sea (AAIS) Workshop W3: Constructing a practical framework of multi-modal imaging frameworks for personalized brain-based interventions Competition Comp1: COVID19 Detection in Blood Exams Competition Comp2: AI Challenge of Alzheimer's disease classification based on multicenter DTI data
|