Concept

Neural network

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BIO-465: Biological modeling of neural networks

In this course we study mathematical models of neurons and neuronal networks in the context of biology and establish links to models of cognition. The focus is on brain dynamics approximated by determ

EE-714: Nonlinear signal modeling and prediction

The literature on nonlinear signal processing has exploded, and it becomes more and more difficult to identify the most useful approaches for specific contexts. This course presents promising developm

PHYS-815: 7th Machine learning in HEP Summer School

The school will cover the relatively young area of data analysis and computational research that has started to emerge in High Energy Physics (HEP). It is known by several names including "Multivariat

MICRO-723: Deep Learning for Optical Imaging

This course will focus on the practical implementation of artificial neural networks (ANN) using the open-source TensorFlow machine learning library developed by Google for Python.

MSE-806: Spin-based devices for neuromorphic computing

The course entails a 5-days-program with lectures and exercises about spin-based computing and novel spin texture-based computing devices. An additional round table discussion and journal club session

FIN-418: Machine learning for finance

This course is introduces machine learning techniques for financial applications in algorithmic trading, derivatives pricing, model calibration, hedging, and risk management. The course format is hand

ChE-650: Artificial intelligence in chemistry and beyond (fall)

Should have expertise in chemistry, physics or lite and material sciences. Although a very good knowledge in Al-based algorithms is required to fully understand the technical details, a basic knowledg

BIO-610: State of the Art Topics in Neuroscience XI

The goal of the course is to increase students' knowledge in the field of Neuroscience, with a particular emphasis on neuronal circuits responsible for sensation, motor control and sensorimotor intera

CS-434: Unsupervised & reinforcement learning in neural networks

Learning is observable in animal and human behavior, but learning is also a topic of computer science. This course links algorithms from machine learning with biological phenomena of synaptic plastic

MATH-631: Mathematical foundations of neural networks

This course is in the form of a reading course / working group. We will focus on some mathematical aspects of the theory of neural networks, including universal approximation theorems, connections to