that’s a wrap for #AI4Mat and #FPIWorkshop at #ICLR2025 🎁 thanks for coming, off to sleep for the next 2 weeks 😴 #FPIWorkshop: Tara Akhound Sadegh Alex Tong Joey Bose Sarthak Mittal Kirill Neklyudov Yuanqi Du #AI4Mat: Santiago Miret Rocío M N M Anoop Krishnan Stefano Martiniani Mohamad Moosavi

Some personal updates: I will be at Boston from May to August this summer and from August to December I will be in Bay Area! Ping me to chat & if there is any fun event in both places or we should organize some together!

The plan at FutureHouse has been to build scientific agents and use them to make novel discoveries. We’ve spent the last year researching the best way to make agents. We’ve made a ton of progress and now we’ve engineered them to be used at scale, by anyone. Today, we’re launching

Some personal updates: 1. I will defend my PhD thesis, "Advancing Artificial Intelligence for Efficient and Synthesizable In-silico Molecular Design," at 10 am on May 9th in MIT 66-110, all are welcome! 2. After a ~1 year postdoc at Stanford, I’ll join the CBE department at UPenn

Another wonderful work from Yinuo Ren!

Nice mechanism! Looking forward to seeing this improving the review quality!

ReactOT featured by Chemistry World! Check out the article!

We’re thrilled to announce the launch of the MolSS Reading Group! 🚀 🔬 MolSS = Machine Learning for Molecular Simulations and Sampling 🔥 First session: June 3rd, 3 PM (UK time) by Jose Miguel Hernández-Lobato 🗓️ Regular sessions: Every other Tuesday at 4 PM (UK time), 45–60 minutes

Obit for Peter Lax nytimes.com/2025/05/16/sci…

Looking forward to sharing FEAT with Jiajun He! Come if you are interested!

📢 Introducing Biomni - the first general-purpose biomedical AI agent. Biomni is built on the first unified environment for biomedical agent with 150 tools, 59 databases, and 106 software packages and a generalist agent design with retrieval, planning, and code as action. This

Our first session will be on next Tuesday (Jan 3rd) from 3pm to 4pm (UK time) 🚀 This session will be given by Jose Miguel Hernández-Lobato , talking about free energy estimation 🔥 Abstract could be found in our slack: join.slack.com/t/molss/shared… Join us via zoom : us05web.zoom.us/j/7780256206?p…

At FutureHouse, we’ve noticed scientific agents are good at applying average intelligence across tasks. They always seem to make the obvious choices, which is good, but discovery sometimes requires more intuition and insight than average. We’ve made the first step today towards

🎉 Thrilled to share our latest work on solving inverse problems via diffusion-based priors — without heuristic approximations of the measurement matching score! 📄 Link: arxiv.org/abs/2506.03979 (1/6) #DiffusionModels #InverseProblems #Guidance #SequentialMonteCarlo

Excited to unveil Boltz-2, our new model capable not only of predicting structures but also binding affinities! Boltz-2 is the first AI model to approach the performance of FEP simulations while being more than 1000x faster! All open-sourced under MIT license! A thread… 🤗🚀

(1/n)🚨You can train a model solving DFT for any geometry almost without training data!🚨 Introducing Self-Refining Training for Amortized Density Functional Theory — a variational framework for learning a DFT solver that predicts the ground-state solutions for different

"Statistical mechanics: entropy, order parameters, and complexity" available as PDF from the author home page: sethna.lassp.cornell.edu/StatMech/

🚀🚀🚀 Sharing a new exciting work! Nature teaches us to think not only in forward, but also in backward. The counterintuitive backward process gives so much strength, not only in understanding out-of-equilibrium process, but also controlling and estimating with diffusion models!

You may already be amazed by diffusion models for generating images and videos—but did you know they can also help wildlife conservation🐘? We propose DiffOracle, combining diffusion models & game theory to stop poaching! Arxiv: arxiv.org/abs/2503.05730

🚀 After two+ years of intense research, we’re thrilled to introduce Skala — a scalable deep learning density functional that hits chemical accuracy on atomization energies and matches hybrid-level accuracy on main group chemistry — all at the cost of semi-local DFT. ⚛️🔥🧪🧬