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Gatsby Computational Neuroscience Unit

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Current and Past Gatsby Unit Course Materials

 
 
Current

Term 1 courses from week of 2 October 2023
Probabilistic and Unsupervised Learning & Approximate Inference and Learning in Probabilistic Models
Systems and Theoretical Neuroscience (co-taught with SWC) (intranet, access to Gatsby and SWC members only)
Kernel Methods and Theory of Machine Learning

Term 2/3 courses from week of 9 January 2024
Theoretical Neuroscience

Lectures are held in the SWC Ground Floor Lecture Theatre (25 Howland St).

2022 - 2023

Term 1 courses from week of 3 October 2022
Systems and Theoretical Neuroscience (co-taught with SWC) (intranet, access to Gatsby and SWC members only)
Kernel Methods and Theory of Machine Learning

Term 2 courses from week of 9 January 2023
Theoretical Neuroscience - lectures are held in the Gatsby seminar room (3rd floor, SWC building)
Reinforcement Learning (CSML)

2021 – 2022

Term 1 courses
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models
Systems and Theoretical Neuroscience (co-taught with SWC)
Kernel Methods and Theory of Machine Learning

Term 2
Theoretical Neuroscience
Reinforcement Learning (CSML)

2020 – 2021

Term 1 courses
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models
Systems and Theoretical Neuroscience (co-taught with SWC)
Kernel Methods and Theory of Machine Learning

Term 2
Theoretical Neuroscience
Reinforcement Learning (CSML)

2019 – 2020

Term 1 courses from week of 30 September 2019
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models
Systems and Theoretical Neuroscience (co-taught with SWC)
Kernel Methods and Theory of Machine Learning (co-taught with CSML)

Term 2 courses
Theoretical Neuroscience
Reinforcement Learning (CSML)

All lectures will be held in the Ground Floor Seminar Room, 25 Howland Street.

2018 – 2019

Term 1 courses from week of 1 October 2018
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models
Systems and Theoretical Neuroscience (co-taught with SWC)
Kernel Methods and Theory of Machine Learning (co-taught with CSML)

Term 2 courses
Theoretical Neuroscience
Neural Data Modelling

All lectures are held in the Ground Floor Seminar Room, 25 Howland Street, London. W1T 4JG.

2017 – 2018

Term 1 courses from week of 2rd October 2017
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models
Systems and Theoretical Neuroscience (co-taught with SWC)
Kernel Methods and Theory of Machine Learning (co-taught with CSML)

Term 2 courses
Systems and Theoretical Neuroscience (co-taught with SWC)
Neural Data Modelling

All lectures are held in the Ground Floor Seminar Room, 25 Howland Street, London. W1T 4JG.

2016 – 2017

 

 

Term 1 courses from week of 3rd October 2016
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models

Term 2 courses from week of 23rd January 2017
Theoretical Neuroscience
Neural Data Modelling

All lectures are held in the Ground Floor Seminar Room, 25 Howland Street, London. W1T 4JG.

2015 – 2016

 

 

Theoretical Neuroscience
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models 

Note: The courses will start on the 5th October 2015 and run in the same format as in previous years, but in a new location: Ground Floor Seminar Room, 25 Howland Street, London. W1T 4JG.

2014 – 2015

 

 

Theoretical Neuroscience 
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models

2013 – 2014

 

 

Theoretical Neuroscience
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models

2012 – 2013

 

 

Theoretical Neuroscience
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models

2011 – 2012

 

 

Theoretical Neuroscience
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models
2010 – 2011

 

 

Theoretical Neuroscience 
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models
2009 – 2010

 

 

Theoretical Neurosience (part I)
Probabilistic and Unsupervised Learning
Approximate Inference and Learning in Probabilistic Models
Machine Learning II & Journal Club
2008 – 2009

 

 

Theoretical Neuroscience (part I) 
Probabilistic & Unsupervised Learning
Machine Learning II
2007 – 2008

 

 

Theoretical Neuroscience (part I)
Probabilistic & Unsupervised Learning
Machine Learning II
2006 – 2007

 

 

Theoretical Neuroscience (part I)
Unsupervised Learning
2005 – 2006

 

 

Theoretical Neuroscience (part I)
Unsupervised Learning
Theoretical Neuroscience (part II)
2004 – 2005

 

 

Theoretical Neuroscience (part I)
Unsupervised Learning
Supervised Learning
Theoretical Neuroscience (part II)