Research Seminar

The research seminar at the Machine Learning section meets roughly once a month to explore topics of interest across the various specializations represented within the research groups. Doctoral and post-doctoral fellows represent the 'prototypical' target audience, but everyone is welcome to participate.


The seminar is organized by doctoral fellow Milena Pavlovic (of the BMI research group), supported by an advisory board of fellows Kristine Baluka Hein (DSB), Frank Veenstra (ROBIN), and Vinit Ravishankar (LTG).

Seminar announcements are distributed through the mailing list , to which all interested parties are welcome to self-subscribe through the on-line interface using their institutional email.

Autumn 2020

Date Hour Room Speaker / Topic
Friday, September 25 14.00 - 15.00 Zoom Johan Pensar: Computational Causal Inference with Bayesian Networks
Friday, October 23 14.00 - 15.00 Zoom

Ulysse Côté-Allard: Transfer learning for biosignal-based control systems

Friday, November 27 14.00 - 15.00 Zoom Hubert Ramsauer: Hopfield Networks is All You Need
Friday, December 18 14.00 - 15.00 Zoom TBA

Spring 2020

Date Hour Room Topic (s)
Friday, February 28 14:00 - 15:00 Prologue (OJD-2465)
Friday, May 22 14:00 - 15:00 Zoom Gabriel Balaban : Causality and confounder analysis in machine learning
Friday, June 5 14:00 - 15:00 Zoom Kristine Baluka Hein : Interpretability and explainability in machine learning
Friday, June 19 14:00 - 15:00 Zoom Vinit Ravishankar : Transformers
Published Feb. 29, 2020 3:04 PM - Last modified Oct. 13, 2020 11:20 AM