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Reposted by Marta Skreta

Rocío Mercado Oropeza @rociomer.bsky.social · Aug 5

📄📄📄 The AI4Mat-NeurIPS-2025 workshop is now open for submissions until August 22, 2025 (AOE)!

Consider submitting full-length papers or shorter-length findings. We also have a special track for papers on benchmarking AI for materials design.

sites.google.com/view/ai4mat/...

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Rocío Mercado Oropeza @rociomer.bsky.social · Apr 28

Thanks to all the speakers and participants for the engaging discussions today, and for making the AI4Mat@ICLR 2025 workshop a great success! Thanks also to Santiago, @martaowesyou.bsky.social, and the rest of the co-organizing team for the effort putting this together. Great to be a part of it!

Singapore EXPO sign outside of the convention center where ICLR was held.

Co-organizer photo with Santiago, myself, and Marta at the end of the workshop.

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Stefan P. Schmid @spschmid.bsky.social · Mar 3

🚀 Looking for reaction conditions that work well for multiple substrates? CurryBO can help🍛

Now out on arXiv: arxiv.org/abs/2502.18966

A short explanation thread 👇

One Set to Rule Them All: How to Obtain General Chemical Conditions via Bayesian Optimization over Curried Functions

General parameters are highly desirable in the natural sciences - e.g., chemical reaction conditions that enable high yields across a range of related transformations. This has a significant practical...

arxiv.org

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Alán Aspuru-Guzik @aspuru.bsky.social · Jan 24

We at @digital-discovery.bsky.social are very happy to announce a new paper type called "Commit". Inspired by version control systems such as git, the idea is that if you have an update on a short and pointed publication, you can send it as a commit. We envision commits to be co-cited with the

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Alán Aspuru-Guzik @aspuru.bsky.social · Jan 21

Excited to have #selfdrivinglaboratories listed as one of the seven technologies to watch in 2025 by @nature.com Thanks to the #matterlab, the @accelerationc.bsky.social and of course all the global community on SDLs! @uoft.bsky.social @vectorinst.bsky.social l

www.nature.com/articles/d41...

Self-driving laboratories, advanced immunotherapies and five more technologies to watch in 2025

Sustainability and artificial intelligence dominate our seventh annual round-up of exciting innovations.

www.nature.com

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Reposted by Marta Skreta

lebellig @lebellig.bsky.social · Jan 5

"The Superposition of Diffusion Models using the Îto Density Estimator" (@martaowesyou.bsky.social, @lazaratan.bsky.social et al.)
It's nice to see an easy-to-compute log-likelihood estimator for SDE sampling of diffusion models (not just ODE)

📄 arxiv.org/abs/2412.17762
🐍 github.com/necludov/sup...

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Joey Bose @joeybose.bsky.social · Dec 28

New paper just dropped! How do you combine pre-trained diffusion models without having to train a new one 🤓?

Turns out you can use our all new Ito density estimator 🔥 to compute densities under a diffusion model efficiently 🚀!

Kirill Neklyudov @k-neklyudov.bsky.social · Dec 28

🧵(3/7)This is all due to an amazing team: @martaowesyou.bsky.social @lazaratan.bsky.social @joeybose.bsky.social @alextong.bsky.social

📄Paper: arxiv.org/abs/2412.17762
💻Code: github.com/necludov/sup...
🤗HuggingFace: huggingface.co/superdiff

The Superposition of Diffusion Models Using the Itô Density Estimator

The Cambrian explosion of easily accessible pre-trained diffusion models suggests a demand for methods that combine multiple different pre-trained diffusion models without incurring the significant co...

arxiv.org

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Marta Skreta @martaowesyou.bsky.social · Dec 28

Work with an absolute dream of a team: @lazaratan.bsky.social @joeybose.bsky.social @alextong.bsky.social and @k-neklyudov.bsky.social 🤗🚀⚡️

📄Paper: arxiv.org/abs/2412.17762
💻Code: github.com/necludov/sup...
🤗HuggingFace: huggingface.co/superdiff

The Superposition of Diffusion Models Using the Itô Density Estimator

The Cambrian explosion of easily accessible pre-trained diffusion models suggests a demand for methods that combine multiple different pre-trained diffusion models without incurring the significant co...

arxiv.org

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Marta Skreta @martaowesyou.bsky.social · Dec 28

Super super excited to share our work SuperDiff 🦹‍♀️ for superimposing pretrained diffusion models at inference time 💪

Check out the 🧵 to see how we superimposed proteins as well as images, all thanks to a fast new density estimator. Curious to see what 🍩 & 🗺️ would produce?

Kirill Neklyudov @k-neklyudov.bsky.social · Dec 28

🧵(1/7) Have you ever wanted to combine different pre-trained diffusion models but don't have time or data to retrain a new, bigger model?

🚀 Introducing SuperDiff 🦹‍♀️ – a principled method for efficiently combining multiple pre-trained diffusion models solely during inference!

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Marta Skreta @martaowesyou.bsky.social · Dec 18

exciting new workshop announcement!! join us in Singapore for Frontiers in Probabilistic Inference: Learning Meets Sampling 🌏⚡️😃 details below 👇 #ICLR2025

Joey Bose @joeybose.bsky.social · Dec 18

🔊 Super excited to announce the first ever Frontiers of Probabilistic Inference: Learning meets Sampling workshop at #ICLR2025 @iclr-conf.bsky.social!

🔗 website: sites.google.com/view/fpiwork...

🔥 Call for papers: sites.google.com/view/fpiwork...

more details in thread below👇 🧵

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Marta Skreta @martaowesyou.bsky.social · Dec 9

3/3 🧵Work with my fellow Matter Lab quantum tunnelers: Philipp Schleich, Lasse B. Kristensen, @rovargash.bsky.social, @aspuru.bsky.social

📜 https://buff.ly/4iu8w6M
💻 https://buff.ly/3D9HaD2

See you at NeurIPS!

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Marta Skreta @martaowesyou.bsky.social · Dec 9

2/3 🧵Here, we enter the quantumverse with deep equilibrium networks, where we demonstrate that a single layer of a quantum circuit can perform as well or better than multiple independent layers when trained like a DEQ.

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Marta Skreta @martaowesyou.bsky.social · Dec 9

1/3 🧵Quantum conundrum: we want expressive circuits, but current hardware only allows short coherence times, and so more parameters = more problems. Check out our #NeurIPS2024 paper “Quantum Deep Equilibrium Models”.

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