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From Wulfram Gerstner
No BackProp, Please! How can a biological network learn deep representations without Backprop? This video shows that biologically plausible learning rules with a… -
From Wulfram Gerstner
Introduction to Biological Background:From Biological to Artificial Neural Networks -
From Wulfram Gerstner
Three-factor learning rules:Three-factor rules add to Hebbian rules a neuromodulator that conveys a global feedback signal. -
From Wulfram Gerstner
Hebb Rule: a framework for learning rules -
From Wulfram Gerstner
Biological Learning means Synaptic Plasticity -
From Wulfram Gerstner
No Backprop, please !BackProp is the most widely used algorithm in machine learning and artificial neural networks, but it is biologically not plausible. Why? And are… -
From Wulfram Gerstner
The formalism of low-rank recurrent neural networks is introduced. It is shown that trajectories of the dynamics of all N neurons stays in a D-dimensional space, if the… -
From Wulfram Gerstner
This video presents two views of neural activity. The first view is the classic view in the tradition of Hubel and Wiesel, i.e., neurons have characteristic functional… -
From Wulfram Gerstner
Neural Manifold is the name used by neuroscientists for the following observation: when experimentalists record from, say, N = 500 neurons, the activity vector of all N…
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- Home
- EPFL Moocs
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EPFL courses
- Architecture - AR
- Euler courses
- Life sciences - BIO
- Life Sciences Engineering - BIOENG
- Chemistry - CH
- Chemical engineering - ChE
- Civil engineering - CIVIL
- Communication Systems - COM
- Computer Science - CS
- Digital Humanities - DH
- Electrical Engineering - EE
- Engineering - ENG
- Environmental Sciences and Engineering - ENV
- Finance - FIN
- Humanities - HUM
- Quantum sciences and engineering - QUANT
- Materials Science and Engineering - MA
- Mathematics - MATH
- Mechanical Engineering - ME
- Management Technology and Entrepreneurship - MGT
- Microengineering and microsystems - MICRO
- Materials Science and Engineering - MSE
- Neuro-x - NX
- Design Together - PENS
- Preparatory Year - PREPA
- Physics - PHYS
- EPFL miscellaneous
- Mediaspace@EPFL
- Kaltura Help
- Ask for a channel to add videos
- Live courses recordings
Since 2010 approaches in deep learning have revolutionized fields as diverse as computer vision, machine learning, or artificial intelligence. This course gives a systematic introduction into influential models of deep artificial neural networks, with a focus on Reinforcement Learning.
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