Neural Network Activity: Modeling and Analysis

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Building Physical Neural Networks

Discusses challenges in building physical neural networks, focusing on depth, connections, and trainability.

Modeling the Brain: Machine Learning and Neuroscience

Explores the synergy between machine learning and neuroscience, showcasing how deep neural networks can predict neural responses and the challenges faced by AI in robotics.

Neural Signals and Signal Processing

Covers neural signals, brain enthusiasm, neuroimaging, and statistical analysis in neuroimaging studies.

Associative Memory: Magnetic Materials

Explores the dynamics of associative memory in networks of neurons and includes a detour into magnetic materials.

Neural Model: Assemblies of Neurons and Language Acquisition

Explores a neural model, assemblies of neurons, language acquisition, and the future of neuromorphic intelligent systems.

Nonlinear Supervised Learning

Explores the inductive bias of different nonlinear supervised learning methods and the challenges of hyper-parameter tuning.

Towards trainable bio-robots

Explores the development of bio-robots using programmable biological neural processors.

Optimization of Neuroprosthetic Systems

Explores the optimization of neuroprosthetic systems, including sensory feedback restoration and neural stimulation strategies.

AdEx model: Firing patterns and phase plane analysis

Explores the AdEx neuron model, analyzing firing patterns and phase planes.

Neural Networks: Basics and Applications

Explores neural networks basics, XOR problem, classification, and practical applications like weather data prediction.