Paper: arxiv.org/abs/2409.16797

Code: github.com/AlexanderRub...

OpenReview: openreview.net/forum?id=BQE...

Thank Alex for his great efforts and work ethic. Thank @damienteney.bsky.social and @lucascimeca.bsky.social for their continued help with this paper. We’ll humbly address the criticisms to improve it further for future opportunities.

We were a bit unlucky with the reviewers - one voted for acceptance, while the other two remained silent during the discussion phase. What matters, though, is knowing this is solid work and the method works. That’s how we survive the review process.

- Outcome: Scaled ensemble diversification to ImageNet level, achieving improved OOD generalisation and detection.

If you can't wait for the arXiv version, check out the ICLR forum: openreview.net/forum?id=ByC...

PS: This paper had 6 reviewers, unanimously voting for acceptance eventually (score 6+). Such luck is rare for me 😅 I'm glad that the hard work paid off, @auselis.bsky.social. Let's arXiv it!

Thank other co-authors too: Alexander Rubinstein and Ehsan Abbasnejad.

paper: arxiv.org/abs/2403.07968
code: github.com/aktsonthalia...

I.e., at a reasonable width (no wideresnet), solutions already form a star domain.

Side note: We developed a method for finding the "star model", a special solution connected to all other solutions. I couldn't resist naming it "NeuralStarLink" but fortunately the first author Ankit held me back :)

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