New preprint! 🚨 We scale equilibrium sampling to hexapeptide (in cartesian coordinates!) with Sequential Boltzmann generators!  📈 🤯 Work with Joey Bose, Chen Lin, Leon Klein, Michael Bronstein and Alex Tong Thread 🧵 1/11

We are recruiting a colleague to our division at Chalmers in Data-Driven Life Science (broadly defined), a competitive starting package is offered and you get to be part of a support, yet young and ambitious research environment.

Hello from Singapore 🇸🇬! Thrilled to be at #ICLR2025 presenting our work on fragment-based drug discovery 🧩. We go beyond virtual screening with a generative, structure-aware approach. 📃 openreview.net/forum?id=bZW1H… 🔗 github.com/rneeser/Latent… A thread 🧵👇

Excited to present our poster on Boltzmann Priors for Implicit Transfer Operators tomorrow at ICLR 2026! See you tomorrow at poster 13, 10-12:30.

Registration for this years CHAIR Structured Learning Workshop is open. Speakers include: Klaus Robert Müller, Jens Sjölund, Alex Tong, Jan Stühmer Arnaud Doucet, Marco Cuturi, Marta Betcke, Elena Agliari, Beatriz Seoane, Alessandro Ingrosso, ui.ungpd.com/Events/60bfc7b…

Huge thanks to the #ICLR2025 Organizing Committee (including many who couldn't make it to the conference) 👏👏👏

I’m in Thailand for AISTATS and will be presenting our work on SemlaFlow — designing efficient equivariant models for 3D molecular generation (poster session 2, no 132). Come and say hi if you’re around!

Finally out! We have been working on a generative molecular design framework to allow steerable and granular control over synthetic routes for property-optimized molecules. ⚗️ 🖥️ Take a look below! 👇

Ever felt like Boltzmann Generators trained with Flow Matching were doing fine, just not good enough? We slapped Path Gradients on top, and things got better. No extra samples, no extra compute, no changes to the model. Just gradients you already have access to.

New preprint alert 🚨 How can you guide diffusion and flow-based generative models when data is scarce but you have domain knowledge? We introduce Minimum Excess Work, a physics-inspired method for efficiently integrating sparse constraints. Thread below 👇arxiv.org/abs/2505.13375

We are looking for someone to join the group as a postdoc to help us with scaling implicit transfer operators. If you are interested in this, please reach out to me through email. Include CV, with publications and brief motivational statement. RTs appreciated!

Excited to release FORT, a new regression-based approach for training normalizing flows 🔥! 🔗 Paper available here: arxiv.org/abs/2506.01158 New paper w/ Oscar Davis Jiarui Lu Jian Tang Michael Bronstein Yoshua Bengio Alex Tong Joey Bose 🧵1/6

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… 🤗🚀

The official opening to this position was just posted: chalmers.se/en/about-chalm…

Super excited to introduce "Branched Schrödinger Bridge Matching" (BranchSBM) 🌳, our new framework for learning branched Schrödinger bridge trajectories from a common origin into multiple distinct outcomes! 📄 Preprint: arxiv.org/abs/2506.09007 💻 Code: huggingface.co/ChatterjeeLab/…

Three PhD student positions available in my group: aalto.fi/en/open-positi…

BioEmu now published in Science Magazine !! What is BioEmu? Check out this video: youtu.be/LStKhWcL0VE?si…

📢📢 "La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching" Fully atomistic. Partially latent. Structurally precise. Entirely generative. w/ Tomas Geffner*, Kieran Didi @ICLR*, et al. 📜 Project page & paper: research.nvidia.com/labs/genair/la… 🧵 Thread below... (1/n)

🚀 Come check our poster at ICML GenBio Workshop @ ICML25! We show that pretrained MLIPs can accelerate training of Boltzmann emulators — by aligning their internal representations. Coauthors PINEDE Lucas, Juno Nam, RGB Lab @ MIT (1/n)

Our development of machine-learned transferable coarse-grained models in now on Nat Chem! doi.org/10.1038/s41557… I am so proud of my group for this work! Particularly first authors Nick Charron, Klara Bonneau, Aldo S. Pasos-Trejo, Andrea Guljas.