Difference between revisions of "IJCNN 2020"
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{{Event | {{Event | ||
|Acronym=IJCNN 2020 | |Acronym=IJCNN 2020 | ||
+ | |Title=IEEE International Joint Conference on Neural Networks | ||
|Series=IJCNN | |Series=IJCNN | ||
− | | | + | |Type=Conference |
+ | |Start date=2020/07/19 | ||
+ | |End date=2020/07/24 | ||
+ | |Homepage=https://wcci2020.org/ijcnn-sessions/ | ||
|City=Glasgow | |City=Glasgow | ||
|Country=UK | |Country=UK | ||
− | |||
− | |||
− | |||
}} | }} | ||
+ | The International Joint Conference on Neural Networks (IJCNN) covers a wide range of topics in the field of neural networks, from biological neural networks to artificial neural computation. | ||
+ | |||
+ | List of topics: | ||
+ | |||
+ | NEURAL NETWORK MODELS | ||
+ | * Feedforward neural networks | ||
+ | * Recurrent neural networks | ||
+ | * Self-organizing maps | ||
+ | * Radial basis function networks | ||
+ | * Attractor neural networks and associative memory | ||
+ | * Modular networks | ||
+ | * Fuzzy neural networks | ||
+ | * Spiking neural networks | ||
+ | * Reservoir networks (echo-state networks, liquid-state machines, etc.) | ||
+ | * Large-scale neural networks | ||
+ | * Learning vector quantization | ||
+ | * Deep neural networks | ||
+ | * Randomized neural networks | ||
+ | * Other topics in artificial neural networks | ||
+ | |||
+ | MACHINE LEARNING | ||
+ | * Supervised learning | ||
+ | * Unsupervised learning and clustering, (including PCA, and ICA) | ||
+ | * Reinforcement learning and adaptive dynamic programming | ||
+ | * Semi-supervised learning | ||
+ | * Online learning | ||
+ | * Probabilistic and information-theoretic methods | ||
+ | * Support vector machines and kernel methods | ||
+ | * EM algorithms | ||
+ | * Mixture models, ensemble learning, and other meta-learning or committee algorithms | ||
+ | * Bayesian, belief, causal, and semantic networks | ||
+ | * Statistical and pattern recognition algorithms | ||
+ | * Sparse coding and models | ||
+ | * Visualization of data | ||
+ | * Feature selection, extraction, and aggregation | ||
+ | * Evolutionary learning | ||
+ | * Hybrid learning methods | ||
+ | * Computational power of neural networks | ||
+ | * Deep learning | ||
+ | * Other topics in machine learning | ||
+ | |||
+ | NEURODYNAMICS | ||
+ | * Dynamical models of spiking neurons | ||
+ | * Synchronization and temporal correlation in neural networks | ||
+ | * Dynamics of neural systems | ||
+ | * Chaotic neural networks | ||
+ | * Dynamics of analog networks | ||
+ | * Itinerant dynamics in neural systems | ||
+ | * Neural oscillators and oscillator networks | ||
+ | * Dynamics of attractor networks | ||
+ | * Other topics in neurodynamics | ||
+ | |||
+ | COMPUTATIONAL NEUROSCIENCE | ||
+ | * Connectomics | ||
+ | * Models of large-scale networks in the nervous system | ||
+ | * Models of neurons and local circuits | ||
+ | * Models of synaptic learning and synaptic dynamics | ||
+ | * Models of neuromodulation | ||
+ | * Brain imaging | ||
+ | * Analysis of neurophysiological and neuroanatomical data | ||
+ | * Cognitive neuroscience | ||
+ | * Models of neural development | ||
+ | * Models of neurochemical processes | ||
+ | * Neuroinformatics | ||
+ | * Brain Informatics | ||
+ | * Other topics in computational neuroscience | ||
+ | |||
+ | NEURAL MODELS OF PERCEPTION, COGNITION AND ACTION | ||
+ | * Neurocognitive networks | ||
+ | * Cognitive architectures | ||
+ | * Models of conditioning, reward and behavior | ||
+ | * Cognitive models of decision-making | ||
+ | * Embodied cognition | ||
+ | * Cognitive agents | ||
+ | * Multi-agent models of group cognition | ||
+ | * Developmental and evolutionary models of cognition | ||
+ | * Visual system | ||
+ | * Auditory system | ||
+ | * Olfactory system | ||
+ | * Other sensory systems | ||
+ | * Attention | ||
+ | * Learning and memory | ||
+ | * Spatial cognition, representation and navigation | ||
+ | * Semantic cognition and language | ||
+ | * Grounding, symbol grounding | ||
+ | * Neural models of symbolic processing | ||
+ | * Reasoning and problem-solving | ||
+ | * Working memory and cognitive control | ||
+ | * Emotion and motivation | ||
+ | * Motor control and action | ||
+ | * Dynamical models of coordination and behavior | ||
+ | * Consciousness and awareness | ||
+ | * Models of sleep and diurnal rhythms | ||
+ | * Mental disorders | ||
+ | * Other topics in neural models of perception, cognition and action | ||
+ | |||
+ | NEUROENGINEERING | ||
+ | * Brain-machine interfaces | ||
+ | * Neural prostheses | ||
+ | * Neuromorphic hardware | ||
+ | * Embedded neural systems | ||
+ | * Other topics in neuroengineering | ||
+ | |||
+ | BIO-INSPIRED AND BIOMORPHIC SYSTEMS | ||
+ | * Brain-inspired cognitive architectures | ||
+ | * Embodied robotics | ||
+ | * Evolutionary robotics | ||
+ | * Developmental robotics | ||
+ | * Computational models of development | ||
+ | * Collective intelligence | ||
+ | * Swarms | ||
+ | * Autonomous complex systems | ||
+ | * Self-configuring systems | ||
+ | * Self-healing systems | ||
+ | * Self-aware systems | ||
+ | * Emotional computation | ||
+ | * Artificial life | ||
+ | * Other topics in bio-inspired and biomorphic systems | ||
+ | |||
+ | APPLICATIONS | ||
+ | * Applications of deep neural networks | ||
+ | * Bioinformatics | ||
+ | * Biomedical engineering | ||
+ | * Data analysis and pattern recognition | ||
+ | * Speech recognition and speech production | ||
+ | * Robotics | ||
+ | * Neurocontrol | ||
+ | * Approximate dynamic programming, adaptive critics, and Markov decision processes | ||
+ | * Neural network approaches to optimization | ||
+ | * Signal processing, image processing, and multi-media | ||
+ | * Temporal data analysis, prediction, and forecasting; time series analysis | ||
+ | * Communications and computer networks | ||
+ | * Data mining and knowledge discovery | ||
+ | * Power system applications | ||
+ | * Financial engineering applications | ||
+ | * Security applications | ||
+ | * Applications in multi-agent systems and social computing | ||
+ | * Manufacturing and industrial applications | ||
+ | * Expert systems | ||
+ | * Clinical applications | ||
+ | * Big data applications | ||
+ | * Other applications | ||
+ | * Smart grid applications | ||
+ | |||
+ | CROSS-DISCIPLINARY TOPICS | ||
+ | * Hybrid intelligent systems | ||
+ | * Swarm intelligence | ||
+ | * Sensor networks | ||
+ | * Quantum computation | ||
+ | * Computational biology | ||
+ | * Molecular and DNA computation | ||
+ | * Computation in tissues and cells | ||
+ | * Artificial immune systems | ||
+ | * Philosophical issues | ||
+ | * Other cross-disciplinary topics |
Latest revision as of 14:58, 6 March 2020
IJCNN 2020 | |
---|---|
IEEE International Joint Conference on Neural Networks
| |
Event in series | IJCNN |
Dates | 2020/07/19 (iCal) - 2020/07/24 |
Homepage: | https://wcci2020.org/ijcnn-sessions/ |
Location | |
Location: | Glasgow, UK |
Loading map... | |
Table of Contents | |
The International Joint Conference on Neural Networks (IJCNN) covers a wide range of topics in the field of neural networks, from biological neural networks to artificial neural computation.
List of topics:
NEURAL NETWORK MODELS
- Feedforward neural networks
- Recurrent neural networks
- Self-organizing maps
- Radial basis function networks
- Attractor neural networks and associative memory
- Modular networks
- Fuzzy neural networks
- Spiking neural networks
- Reservoir networks (echo-state networks, liquid-state machines, etc.)
- Large-scale neural networks
- Learning vector quantization
- Deep neural networks
- Randomized neural networks
- Other topics in artificial neural networks
MACHINE LEARNING
- Supervised learning
- Unsupervised learning and clustering, (including PCA, and ICA)
- Reinforcement learning and adaptive dynamic programming
- Semi-supervised learning
- Online learning
- Probabilistic and information-theoretic methods
- Support vector machines and kernel methods
- EM algorithms
- Mixture models, ensemble learning, and other meta-learning or committee algorithms
- Bayesian, belief, causal, and semantic networks
- Statistical and pattern recognition algorithms
- Sparse coding and models
- Visualization of data
- Feature selection, extraction, and aggregation
- Evolutionary learning
- Hybrid learning methods
- Computational power of neural networks
- Deep learning
- Other topics in machine learning
NEURODYNAMICS
- Dynamical models of spiking neurons
- Synchronization and temporal correlation in neural networks
- Dynamics of neural systems
- Chaotic neural networks
- Dynamics of analog networks
- Itinerant dynamics in neural systems
- Neural oscillators and oscillator networks
- Dynamics of attractor networks
- Other topics in neurodynamics
COMPUTATIONAL NEUROSCIENCE
- Connectomics
- Models of large-scale networks in the nervous system
- Models of neurons and local circuits
- Models of synaptic learning and synaptic dynamics
- Models of neuromodulation
- Brain imaging
- Analysis of neurophysiological and neuroanatomical data
- Cognitive neuroscience
- Models of neural development
- Models of neurochemical processes
- Neuroinformatics
- Brain Informatics
- Other topics in computational neuroscience
NEURAL MODELS OF PERCEPTION, COGNITION AND ACTION
- Neurocognitive networks
- Cognitive architectures
- Models of conditioning, reward and behavior
- Cognitive models of decision-making
- Embodied cognition
- Cognitive agents
- Multi-agent models of group cognition
- Developmental and evolutionary models of cognition
- Visual system
- Auditory system
- Olfactory system
- Other sensory systems
- Attention
- Learning and memory
- Spatial cognition, representation and navigation
- Semantic cognition and language
- Grounding, symbol grounding
- Neural models of symbolic processing
- Reasoning and problem-solving
- Working memory and cognitive control
- Emotion and motivation
- Motor control and action
- Dynamical models of coordination and behavior
- Consciousness and awareness
- Models of sleep and diurnal rhythms
- Mental disorders
- Other topics in neural models of perception, cognition and action
NEUROENGINEERING
- Brain-machine interfaces
- Neural prostheses
- Neuromorphic hardware
- Embedded neural systems
- Other topics in neuroengineering
BIO-INSPIRED AND BIOMORPHIC SYSTEMS
- Brain-inspired cognitive architectures
- Embodied robotics
- Evolutionary robotics
- Developmental robotics
- Computational models of development
- Collective intelligence
- Swarms
- Autonomous complex systems
- Self-configuring systems
- Self-healing systems
- Self-aware systems
- Emotional computation
- Artificial life
- Other topics in bio-inspired and biomorphic systems
APPLICATIONS
- Applications of deep neural networks
- Bioinformatics
- Biomedical engineering
- Data analysis and pattern recognition
- Speech recognition and speech production
- Robotics
- Neurocontrol
- Approximate dynamic programming, adaptive critics, and Markov decision processes
- Neural network approaches to optimization
- Signal processing, image processing, and multi-media
- Temporal data analysis, prediction, and forecasting; time series analysis
- Communications and computer networks
- Data mining and knowledge discovery
- Power system applications
- Financial engineering applications
- Security applications
- Applications in multi-agent systems and social computing
- Manufacturing and industrial applications
- Expert systems
- Clinical applications
- Big data applications
- Other applications
- Smart grid applications
CROSS-DISCIPLINARY TOPICS
- Hybrid intelligent systems
- Swarm intelligence
- Sensor networks
- Quantum computation
- Computational biology
- Molecular and DNA computation
- Computation in tissues and cells
- Artificial immune systems
- Philosophical issues
- Other cross-disciplinary topics
Facts about "IJCNN 2020"
Acronym | IJCNN 2020 + |
End date | July 24, 2020 + |
Event in series | IJCNN + |
Event type | Conference + |
Has coordinates | 55° 51' 40", -4° 14' 56"Latitude: 55.860983333333 Longitude: -4.2488777777778 + |
Has location city | Glasgow + |
Has location country | Category:UK + |
Homepage | https://wcci2020.org/ijcnn-sessions/ + |
IsA | Event + |
Start date | July 19, 2020 + |
Title | IEEE International Joint Conference on Neural Networks + |