AI@MS Journal Club

The format for the journal club is very open ended. Each speaker chooses a paper or a topic of choice that he or she is interested in. It does not have to be a very recent result, but could just was well correspond to some basic part of, say, deep learning, or some open problem that you are thinking about and wish to discuss.

We meat roughly once per month, and every meeting has 1-2 speakers, of about 25 minutes each, including questions/open discussion. The speakers create new posts in Yammer for their talk, including links to relevant papers or other literature. Slides can also be uploaded to the same post after the seminar.

If you want to participate in the journal club please contact Daniel Persson (daniel.persson@chalmers.se) at the Department of Mathematical Sciences.


Past seminars

2019


3/5
Seminar 1: Filip Wikman (Department of Mathematical Sciences)
Title: “Deep learning as an optimal control problem”

Literature: https://arxiv.org/abs/1807.01083
Seminar 2: Rebecka Jörnsten
Title: "Wide neural networks of any depth evolve as linear models under gradient descent"

Literature: https://arxiv.org/abs/1902.06720 

22/3
Anton Johansson (Department of Mathematical Sciences)
Title: “Bayesian Neural Networks”

15/2
Olof Zetterqvist (Department of Mathematical Sciences)
Title: “Finding outliers using the influence function”
Literature: https://arxiv.org/abs/1703.04730 

18/1
Annika Lang (Department of Mathematical Sciences)
Title: “Deepest learning using stochastic partial differential equations”
Literature:  https://arxiv.org/abs/1707.01415  (preprint), https://doi.org/10.1162/neco_a_01094  (journal ref)

2018

14/12
Seminar 1: Jimmy Aronsson (Department of Mathematical Sciences)
Title: “Restricted Boltzmann Machines”
Seminar 2: Fredrik Hellström (Department of Electrical Engineering)
Title: "Neural Loss Surfaces and Local Minima”

23/11
Seminar 1: Petter Mostad (Department of Mathematical Sciences)
Title: "AdaNet: Adaptive Structural Learning”
Literature: https://arxiv.org/pdf/1607.01097.pdf
Seminar 2: Devdatt Dubhashi (Department of Computer Science and Engineering)
Title: "Optimal Transport and Domain Adaptation”


26/10
Seminar 1: Giuseppe Durisi (Department of Electrical Engineering)
Title: "Opening the Black Box of Deep Neural Networks via Information”
Literature: https://arxiv.org/abs/1703.00810
Seminar 2: Christoffer Petersson (Deep Learning Team, Zenuity)
Title: "Measuring the Intrinsic Dimension of Objective Landscapes”
Literature: https://arxiv.org/abs/1804.08838

5/10
Seminar 1: Daniel Persson (Department of Mathematical Sciences)
Title: "Deep Learning and Renormalization”
Literature: https://arxiv.org/abs/1410.3831
Seminar 2: Johan Jonasson (Department of Mathematical Sciences)
Title: “Variational Inference"

Published: Fri 22 Feb 2019. Modified: Fri 10 May 2019