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 firstname.lastname@example.org , to which all interested parties are welcome to self-subscribe through the on-line interface using their institutional email.
|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|
|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|