IJCNN 2020: Session grid

Sunday, July 19th, 2020 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|

Time | IJCNN Room 1 | IJCNN Room 2 | IJCNN Room 3 | IJCNN Room 4 | IJCNN Room 5 | IJCNN Room 6 | IJCNN Room 7 | IJCNN Poster Room 1 | IJCNN Poster Room 2 | IJCNN Workshop |

11:30AM | I-W1: Workshop: Sentic Computing | |||||||||

1:30PM | End of day | |||||||||

Monday, July 20th, 2020 | ||||||||||

Time | IJCNN Room 1 | IJCNN Room 2 | IJCNN Room 3 | IJCNN Room 4 | IJCNN Room 5 | IJCNN Room 6 | IJCNN Room 7 | IJCNN Poster Room 1 | IJCNN Poster Room 2 | IJCNN Workshop |

3:30PM | I-R1: Feedforward neural networks | I-SS1: Randomization-Based Deep and Shallow Learning Algorithms | I-SS22: Learning Representations for Structured Data | I-SS59A: Artificial Intelligence and Advanced Machine Learning for Biomedical Signal Processing | I-SBP: Student Best Paper Award | I-R2: Supervised learning 1 | I-R3: Neurodynamics | I-P1: Feedforward neural networks | I-P2: Applications of deep networks | |

5:30PM | Break | |||||||||

5:45PM | I-R4: Deep neural networks | I-SS2: Data Driven Approach for Bio-medical and Healthcare | I-SS35: Deep and Generative Adversarial Learning | I-SS59B: Artificial Intelligence and Advanced Machine Learning for Biomedical Signal Processing | I-BP : Regular Best Paper Award | I-R5: Supervised learning 2 | I-R6: Cognitive Neuroscience and Neurocognition | I-P3: Recurrent Neural Networks and SOM | I-P4: Applications of deep networks, big data | |

7:45PM | Break | |||||||||

8:00PM | I-R7: Deep neural networks | I-SS3: Current Trend of Machine Learning in Computer Vision | I-SS32: Healthcare Analytics: Improving Healthcare outcomes using Big Data Analytics | I-SS60: Learning from Difficult Data Streams | I-SS36-7: Deep Learning for Wildlife Bioacoustics, Ecology and Crop Science | I-R8: Supervised learning 3 | I-R9: Visual System | I-P5: Different Neural Networks - fuzzy, large scale, RBF | I-P6: Bioinformatics and Biomedical engineering | |

10:00PM | End of day | |||||||||

Tuesday, July 21st, 2020 | ||||||||||

Time | IJCNN Room 1 | IJCNN Room 2 | IJCNN Room 3 | IJCNN Room 4 | IJCNN Room 5 | IJCNN Room 6 | IJCNN Room 7 | IJCNN Poster Room 1 | IJCNN Poster Room 2 | IJCNN Workshop |

2:30PM | I-R10: Deep neural networks | I-SS4A: Feature Extraction and Learning on Image and Text Data | I-SS50: Machine Learning and Deep Learning Approaches to for Ambient Assisted Living | I-SS13: Computational Intelligence for Applied Time Series Forecasting | I-SS39: Challenges in Reservior Computing | I-R11: Supervised learning 4 | I-R12: Attention | I-P7: Spiking Neural Networks | I-P8: Data analysis and pattern recognition | |

4:30PM | Break | |||||||||

4:45PM | I-R13: Deep neural networks | I-SS4B: Feature Extraction and Learning on Image and Text Data | I-SS42: Artificial Neural Networks for Healthcare and Bio-signals Analysis | I-SS12: Cybersecurity in Complex Environments | I-SS49: Validation, Explanation and Correction of Artificial Intelligence Systems | I-R14: Unsupervised learning and clustering 1 | I-R15: Learning, Memory, Spatial Cognition | I-P9: Deep neural networks | I-P10: Speech recognition, speech production, robotics, neurocontrol, optimization | |

6:45PM | Break | |||||||||

7:00PM | I-R16: Deep neural networks | I-SS6: Bayesian Neural Networks: The Interplay between Bayes' Theorem and Neural Networks | I-SS38: Adversarial Machine Learning and Cyber Security | I-SS15A: Deep Learning and Computational Intelligence for Medical Image Analysis | I-SC7: CI in Transactive Energy Management and Smart Energy Network (CITESEN 2020) | I-R17: Unsupervised learning and clustering 2 | I-R18: Semantic Cognition and Symbolic Processing | I-P11: Deep neural networks | I-P12: Signal processing, image processing, and multi-media | |

9:00PM | End of day | |||||||||

Wednesday, July 22nd, 2020 | ||||||||||

Time | IJCNN Room 1 | IJCNN Room 2 | IJCNN Room 3 | IJCNN Room 4 | IJCNN Room 5 | IJCNN Room 6 | IJCNN Room 7 | IJCNN Poster Room 1 | IJCNN Poster Room 2 | IJCNN Workshop |

3:30PM | I-R19: Deep neural networks | I-SS7: Machine Learning Applications in Cyber Security | I-SS40: Complex-valued and Quaternionic Neural Networks: Theory and Applications | I-SS15B: Deep Learning and Computational Intelligence for Medical Image Analysis | I-SC8: CI for Bioinformatics and Computational Biology | I-R20: Reinforcement learning and adaptive dynamic programming 1 | I-R21: Motor Control | I-P13: Deep neural networks | I-P14: Temporal data analysis, prediction and forecasting; time series analysis, computer networks | |

5:30PM | Break | |||||||||

5:45PM | I-R22: Deep neural networks | I-SS9A: Deep Neural Audio Processing | I-SS45: Neural Architecture Search and its Applications | I-SS19: Concept Drift, Domain Adaptation & Learning in Dynamic Environments | I-SC10: Sensors, Robotics and Artificial Intelligence: From Theory to Applications | I-R23: Reinforcement learning and adaptive dynamic programming 2 | I-R24: Applications of deep networks | I-P15: Supervised Learning | I-P16: Data mining and knowledge discovery | |

7:45PM | Break | |||||||||

8:00PM | I-R25: Deep neural networks | I-SS9B: Deep Neural Audio Processing | I-SS41: Neural Architecture Search and Deep Reinforcement Learning for Autonomous Driving | I-SS20: Artificial Intelligence and SEcurity (AISE) | I-SS4-28: AI Technologies in IoT, CI & Software Engineering | I-R26: Semi-supervised learning | I-R27: Data analysis and pattern recognition | I-P17: Supervised Learning | I-P18: Power system and financial engineering applications | |

10:00PM | End of day | |||||||||

Thursday, July 23rd, 2020 | ||||||||||

Time | IJCNN Room 1 | IJCNN Room 2 | IJCNN Room 3 | IJCNN Room 4 | IJCNN Room 5 | IJCNN Room 6 | IJCNN Room 7 | IJCNN Poster Room 1 | IJCNN Poster Room 2 | IJCNN Workshop |

3:30PM | I-R28: Fuzzy and Large Scale neural networks | I-SS10: Recurrent Neural Information Processing: Models and Applications | I-SS46: Intelligent Vehicle and Transportation Systems | I-SS13A: Biologically Inspired Cognitive Robotics | I-SS15: Intelligent Control: Methods and Applications | I-R29: Deep learning I | I-COMP: IJCNN Competitions | I-P19: Unsupervised learning and clustering (including PCA and ICA) | I-P20: Multi-agent systems, social computing, industrial, expert systems | |

5:30PM | Break | |||||||||

5:45PM | I-R30: Modular Networks | I-SS27: Embedded AI for Real-Time Systems | I-SS51: Neurocomputing and Cognition | I-SC13B: Biologically Inspired Cognitive Robotics | I-SS33B: Computationally Intelligent Methods in Neural Data Processing | I-R31: Deep Learning II | I-R32: Applications of deep networks | I-P21: Reinforcement learning and adaptive dynamic programming | I-P22: Clinical applications | |

7:45PM | Break | |||||||||

8:00PM | I-R33: Recurrent neural networks | I-SS25A: Machine Learning and Deep Learning Methods applied to Vision and Robotics | I-SS47: Mind, Brain, and Cognitive Algorithms | I-SS16: Neural Network-based Uncertainty Quantification | I-SS34: Deep Learning for Brain-like Computing and Pattern Recognition | I-R34: Deep Learning III | I-R35: Signal processing, image processing, and multi-media | I-P23: Semi-supervised learning, Online Learning, Probabilistic Methods | I-P24: Other applications | |

10:00PM | End of day | |||||||||

Friday, July 24th, 2020 | ||||||||||

Time | IJCNN Room 1 | IJCNN Room 2 | IJCNN Room 3 | IJCNN Room 4 | IJCNN Room 5 | IJCNN Room 6 | IJCNN Room 7 | IJCNN Poster Room 1 | IJCNN Poster Room 2 | IJCNN Workshop |

2:45PM | I-R36: Reservoir networks and SOM | I-SS18A: Explainable Computational/Artificial Intelligence | I-SS55: Extreme Learning Machines (ELM) | I-SS26: Neuromorphic Sensing, Processing and Applications | I-R37: Applications in multi-agent systems and social computing | I-R38: On-line learning and mixed topics | I-R39: Temporal data analysis, prediction, and forecasting; time series analysis | I-P25: Deep Learning | I-P26: Neurocognitive, visual and auditory systems | |

4:45PM | Break | |||||||||

5:00PM | I-R40: Spiking Neural Networks | I-SS18B: Explainable Computational/Artificial Intelligence | I-SS52: Methods and Applications of Deep Reinforcement Learning to Autonomous Systems | I-SS30: Robustness and Trustworthiness in Deep Learning | I-R41: Manufacturing and industrial applications | I-R42: Mixture models | I-R43: Data mining and knowledge discovery | I-P27: Deep Learning | I-P28: Attention, Memory, Spatial Cognition, computational neuroscience, neurodynamics | |

7:00PM | Break | |||||||||

7:15PM | I-R44: Spiking and Other NN | I-SS25B: Machine Learning and Deep Learning Methods applied to Vision and Robotics | I-SS54: Online Intelligence and Trust Computation in Large-Scale Dynamic Networks | I-SS33A: Computationally Intelligent Methods in Neural Data Processing | I-R45: Expert systems | I-R46: Clinical and Other applications | I-R47: Power system applications | I-P29: Mixture models, ensemble learning | I-P30: Semantic Cognition, emotion, coordination and behavior | |

9:15PM | End of day |

Processed: 2020-10-25 08:54:27 EDT.