[visionlist] Call for abstracts, ICLR workshop "Generalization beyond the training distribution in brains and machines"

christina christina.funke at uni-tuebingen.de
Tue Feb 9 15:53:32 -04 2021

Dear researchers,

For our ICLR workshop “Generalization beyond the training distribution 
in brains and machines <https://iclr2021generalization.github.io/>”, we 
welcome abstract submission for our poster session.

Speakers and panelists include Aleksander Madry, Brenden Lake, Ida 
Mommenejad, Kimberley Stachenfeld, Margaret Livingstone, Matthias 
Bethge, Pawan Sinha, Raquel Urtasun, Shimon Ullman, Thomas Serre, Tomaso 

Topics include but are not limited to systematic generalization, 
out-of-sample / out-of-domain generalization, learning from non-IID / 
long-tail data:

  * Demonstration of success and failure modes in biological
    intelligence versus neural networks or other models for artificial
  * Computational theory for generalization in biological or artificial
  * Mechanisms of biological intelligence that support generalization,
    at the level of cells, circuits, systems, or cognition.
  * Datasets or benchmarks that represent novel challenges for
    biological or artificial intelligence.

Abstracts can contain up to, but not more than 300 words, and may 
include a maximum of 1 figure. Submissions may be work in progress or 
currently under review - as long as the other venue’s rules permit that. 
The format of the submission should be a pdf with the ICLR template 

Abstracts are submitted via CMT 
The submission deadline is March 12th.

Submissions will be evaluated by the workshop organizers. We intend to 
accept the majority of submissions. Reasons for rejection could be an 
inappropriate topic, flawed or no methods, incomprehensibility or 
repetition of known literature.

Accepted abstracts will be presented during the poster session (see 
schedule). They will also be posted on the workshop site, but under a 
non-archival status.

We look forward to receiving your submissions!
The Organizers

Contact for questions and requests: iclr2021generalization at gmail.com

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