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Related lectures (30)

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Neuroscience and AI: Bridging the Gap

Explores the gap between AI and human intelligence through neuroscience-inspired models and algorithms.

Scientific Computing Essentials

Covers algorithmic thinking, Python programming, numerical methods, and essential computing concepts for scientific computing.

Brain Intelligence: Continual Learning of Representational Models

Delves into the continual learning of representational models after deployment, highlighting the limitations of current artificial neural networks.

Introduction to Systems Neuroscience: Memory Systems Overview

Introduces systems neuroscience, focusing on neural circuits, memory systems, and course logistics.

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Neuromorphic Computing: Challenges and Future

Discusses the challenges and future of neuromorphic computing, comparing digital computers and specialized hardware, such as SpiNNaker and NEST, while exploring the Human Brain Project's Neuromorphic Computing Platform.

Visual Extensions in the Workplace

Explores the use of visual extensions, such as virtual reality and augmented reality, in enhancing workplace efficiency and communication.

Efficient Stochastic Numerical Methods

Explores efficient stochastic numerical methods for modeling and learning, covering topics like the Analytical Engine and kinase inhibitors.

Protein Interaction Fingerprinting with Geometric Deep Learning

Explores deciphering protein interaction fingerprints using geometric deep learning and the challenges in computational protein-protein interaction design.