International Workshop on Machine Learning for Understanding the Brain (MLUB) welcomes original and unpublished work on theory, systems, algorithms and applications related to Machine Learning and understanding techniques for modeling and analysis of brain in various modalities, such as, fMRI, sMRI, EEG, MEG, fNIRS, and various forms of microscopy.
Learning and inference on neuroimaging data
Cognitive state classification
Functional Connectivity
Sparse Techniques
Multimodal Learning
Multi-Subject Learning
Efficient Algorithms for Large-Scale Data
Brain Network Embedding
Cognitive Computing
Software Simulation of the Brain
Pattern and Object Recognition
Cognitive Machine Learning
Modeling
Vision Models of the Brain
Memory Model of the Brain
Neural Models of the Brain
Visualization
High-Dimensional Neuroimaging Data Visualization
Brain Network Visualization
Network Summarization
Applications
Resting-State Data Analysis
Task-Based Data Analysis
Diagnosis of Diseases
Brain Computer Interface
05月15日
2017
05月18日
2017
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