Send us your abstracts for the #ICLR2021 Workshop on 𝔾𝕖𝕠𝕞𝕖𝕥𝕣𝕚𝕔𝕒𝕝 𝕒𝕟𝕕 𝕋𝕠𝕡𝕠𝕝𝕠𝕘𝕚𝕔𝕒𝕝 ℝ𝕖𝕡𝕣𝕖𝕤𝕖𝕟𝕥𝕒𝕥𝕚𝕠𝕟 𝕃𝕖𝕒𝕣𝕟𝕚𝕟𝕘 until 𝗠𝗮𝗿 𝟬𝟳 𝗔𝗼𝗘! #MachineLearning #geometry #topology #RepresentationLearning openreview.net/group?id=ICLR.…

Cool writeup of ways to do interactive development jupyter notebook style in Neovim, e/plugins 🥰

Einsum is coming to R! Thanks to Constantin Ahlmann-Eltze (@const-ae.bsky.social) for the great community contribution!

A timely work with Leslie O'Bray, Max Horn, and Karsten Borgwardt. Hope this will inspire a nice discussion in the community!

Doing god's work 💪

Congrats to Bastian and all the best for his new adventures! Working with Bastian is and was an amazing experience🤩 To anybody looking for a position: Don't miss this unique opportunity!

Some said an open-world experience this immersive wasn’t possible. But it’s already here. And you don’t even need silly VR headsets. Introducing, ✨Icelandverse✨ #icelandverse

Looking forward to presenting our work on 𝗧𝗼𝗽𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗚𝗿𝗮𝗽𝗵 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 in the upcoming #ICLR2022 poster session from 11:30am CEST. Join us on Gather.Town if you're into #topology and #MachineLearning. openreview.net/forum?id=oxxUM…

Looking forward to presenting our #ICLR2022 spotlight paper Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions at the poster session on Thursday at 11:30 CEST. arxiv.org/abs/2106.01098 Bastian Grossenbacher-Rieck Max Horn Karsten Borgwardt

📣 At #ICLR2022 (Poster F2) in ~45 minutes 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗳𝗼𝗿 𝗚𝗿𝗮𝗽𝗵 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗠𝗼𝗱𝗲𝗹𝘀: 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀, 𝗣𝗶𝘁𝗳𝗮𝗹𝗹𝘀, 𝗮𝗻𝗱 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 Leslie O'Bray Max Horn Karsten Borgwardt #MachineLearning

In our new paper we conduct a large scale study on out-of-distribution robustness. We evaluate insights around robustness, domain generalization, architecture biases, uncertainty quantification and adversarial examples in a unified setting. arxiv.org/abs/2207.09239

Excellent summary of Neil Stephenson’s books. A great resource for anybody into sci-fi and looking for some new material. Thank you for compiling this Bastian Grossenbacher-Rieck !

A bit late, but still: I'm super happy that my paper on scaling unsupervised object-centric representation learning to the real-world got accepted to #ICLR2023. Our method, DINOSAUR, takes a big step towards open, complex image datasets like PASCAL and COCO!

Cool to see some follow up on this line of research. Great work Bastian!

Btw, we just released OCLF, a flexible codebase for object-centric learning research, containing the code for DINOSAUR and much more. Thanks to Max Horn for the huge amount of work on this! github.com/amazon-science…

Thrilled to see our multi-centre #sepsis prediction study finally published! Thanks to Nicolas Bennett, Drago Plečko, Max Horn Bastian Grossenbacher-Rieck, Nicolai Meinshausen, Peter Bühlmann, and Karsten Borgwardt! ETH Zurich D-BSSE, ETH Zurich @ETH_MATH Personalized Health and Related Technologies thelancet.com/journals/eclin…

Check out this cool work done by Max during his time at Amazon. Was a pleasure having you Max and it’s great to see the work in print!

Looking forward to being at #ICML2024 starting from tomorrow. Feel free to write a PM in case you want to grab a coffee and chat 🙂

Congrats Bastian! Great to have you back in Switzerland🇨🇭 :)