Description

Leader of the group Machine Learning: Peter Grunwald.

Our research group focuses on how computer programs can learn from and understand data, and then make useful predictions based on it. These algorithms integrate insights from various fields, including statistics, artificial intelligence and neuroscience.  

 Machine-learning applications are increasingly part of every aspect of life, from speech recognition on cell phones to illness prediction in healthcare. One common problem is extremely polluted data, for which no single model can provide adequate explanations. At CWI we address this issue with statistical machine learning based on combining predictions from different models and experts in order to achieve reliable conclusions.

We also study how networks of neurons in the brain process information, and how modern deep-learning methods can benefit from neuroscience. We develop novel neural networks, like Deep Adaptive Spiking Neural Networks, and also theoretical models of neural learning and information processing in biology. Applications of our work range from low-energy consumption neural machine learning to neuroprosthetics, to increased insight into the question of how the brain works.

Current Projects

  • Machine Learning at the Intrinsic Task Pace
  • DEVIS
    Deep Spiking Vision: Better, Faster, Cheaper

Events

CWI Lectures on Machine Learning

  • 2017-11-23T12:00:00+01:00
  • 2017-11-23T18:00:00+01:00
November 23 Thursday

Start: 2017-11-23 12:00:00+01:00 End: 2017-11-23 18:00:00+01:00

Turingroom at Congress Centre Amsterdam Science Park

This year, the CWI Lectures will be held on Thursday 23 November. The theme will be Machine Learning and the afternoon will be organized by CWI's newly established Machine Learning group. 

Speakers will include two of the world's leading machine learning researchers: Suchi Saria and Neil Lawrence:

- Suchi Saria is professor at Johns Hopkins University. Even though she only obtained her Ph.D. (at Stanford) in 2011, her work has already attracted considerable attraction and honours. For example, in 2016 she has been selected as 'one of Popular Science's Brilliant 10'. She has also been named one of AI's "ten to watch" by IEEE in 2014. She is, among many other things, known for successful applications of state-of-the-art theory in machine learning and statistics within the health domain. 
- Neil Lawrence is founder and director of Amazon Research Cambridge and professor at Sheffield University. He is a regular contributor to The Guardian where he writes about impact of machine learning technology to society.   He is former program chair of NIPS, the world's main machine learning conference, and is founder of Data Science Africa. 

 

More information about the programme will follow asap.

Registration for the Lectures will open in August.

Members of Machine Learning

Publications

News