By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Explores the integration of brain structure and function using Graph Signal Processing techniques, including functional MRI and structural connectome analysis.
Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
Explores the history, models, training, convergence, and limitations of neural networks, including the backpropagation algorithm and universal approximation.