iiinova — where your digital self keeps evolving

Reposted by Siddharth Mishra-Sharma

Kyle Cranmer @kylecranmer.bsky.social · 31/07/2026

I've been thinking about the Rubik's cube in 4D. I found an old java version from by Don Hatch and Melinda Green and decided to ask claude to port it to a standalone web app that can run in your browser. You can play it here: theoryandpractice.org/cube4d/ Blog: theoryandpractice.org/2026/07/four...

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Reposted by Siddharth Mishra-Sharma

Kyle Cranmer @kylecranmer.bsky.social · 10/07/2025

🎉 Great news: Our Machine Learning and Physical Sciences workshop will be back again this year! 🎉 Keep an eye out for updates on deadlines etc, we will be updating the website soon ml4physicalsciences.github.io #ML4PS2025

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Siddharth Mishra-Sharma @smsharma.bsky.social · 05/01/2025

Are you using the API or Console (console.anthropic.com) to get more Claude? (Happy to pass along any feedback...)

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Reposted by Siddharth Mishra-Sharma

Gilles Louppe @glouppe.bsky.social · 30/12/2024

📣 Hiring! I am looking for PhD/postdoc candidates to work on foundation models for science at @ULiege, with a special focus on weather and climate systems. 🌏 Three positions are open around deep learning, physics-informed FMs and inverse problems with FMs.

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Siddharth Mishra-Sharma @smsharma.bsky.social · 29/12/2024

Yah agreed! Opportunity cost aside, I think a generally nice time as a postdoc, then going to industry seems good from a happiness perspective. It seems likely that regret here mostly reflects a less-than-ideal experience post-PhD (by default for systemic reasons).

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Siddharth Mishra-Sharma @smsharma.bsky.social · 29/12/2024

(If true) I think that's a very specific case, I think industry employers generally don't care or might even weakly prefer fewer years post-PhD

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Reposted by Siddharth Mishra-Sharma

Kyle Cranmer @kylecranmer.bsky.social · 16/12/2024

Got a photo with a nice branch of my academic family tree: @awehwe.bsky.social @glouppe.bsky.social @smsharma.bsky.social @lukasheinrich.com Nicole Hartman @annalenakofler.bsky.social

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Reposted by Siddharth Mishra-Sharma

Kyle Cranmer @kylecranmer.bsky.social · 10/12/2024

The papers and posters for our Machine Learning and Physical Sciences workshop at #NeurIPS2024 are online #ml4ps2024. Come check it out on Sunday ml4physicalsciences.github.io/2024/

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Siddharth Mishra-Sharma @smsharma.bsky.social · 10/12/2024

Poster 4.15, talk 2.30! (Is the schedule shown differently somewhere?)

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Siddharth Mishra-Sharma @smsharma.bsky.social · 04/12/2024

Looking forward to catching up with friends and colleagues at NeurIPS next week, as well as meeting new folks -- feel free to reach out ☕!

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Siddharth Mishra-Sharma @smsharma.bsky.social · 04/12/2024

One hypothesis is that the explicit coarse-graining hurts expressivity, which is preserved when modeling long-range correlations implicitly via the vanilla MPGNN. But not sure -- maybe it's possible to set-up a PointNet-style model to do better!

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Siddharth Mishra-Sharma @smsharma.bsky.social · 04/12/2024

Yep, there are long range correlations in the data, and the global parameter $\sigma_8$ should be especially sensitive to them. Indeed PointNet++ doesn't seem to do very well at capturing them despite explicitly having hierarchical downsampling.

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Siddharth Mishra-Sharma @smsharma.bsky.social · 26/11/2024

Fun paper led by Julia Balla: "A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing". Julia will be presenting the paper at LoG on Thursday as a spotlight oral, and also at the NeurReps Workshop at NeurIPS Workshop next month. 📄: arxiv.org/abs/2410.20516 💻: github.com/smsharma/eqn...

arxiv.org

A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing

Efficiently processing structured point cloud data while preserving multiscale information is a key challenge across domains, from graphics to atomistic modeling. Using a curated dataset of simulated ...

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