Rebecca Neeser

Generate property-optimized small molecules with 𝘴𝘵𝘦𝘦𝘳𝘢𝘣𝘭𝘦 𝘢𝘯𝘥 𝘨𝘳𝘢𝘯𝘶𝘭𝘢𝘳 synthesizability control - allowing complete user-flexibility to impose various reaction constraints! Pre-print: arxiv.org/abs/2505.08774 Code: github.com/schwallergroup… (1/4)

This week we're in #ICLR2025 in Singapore 🇸🇬!! Do reach out to discuss the future of #AI and #Chemistry 🥂 llms, agents, new tools for chemists and new ways of doing chemistry 🚀

Excited to be at #ICLR2025 and happy to chat about ML and drug discovery! 🇸🇬 Come find me at one of our posters or feel free to reach out directly! 1. DrugFlow: #9 Thu 24/04 10am 2. SynFlowNet: #15 Fri 25/04 10am 3. LDDM: @gembioworkshop 27/04 4. LatentFrag: #AI4MAT 28/04

We'll be presenting the poster tomorrow (Thu 24/04) at 10am #ICLR2025. Please come and say hi :) iclr.cc/virtual/2025/p… @igashov @AdrDobbel

🚨New preprint! ✨My precious✨ GOLLuM: GP-Optimized LLMs for Bayesian Optimization — the first of its kind! LLMs as deep kernels in GPs jointly optimized via marginal likelihood → implicit metric learning, calibrated uncertainty & superior sampling 🚀 📄 arxiv.org/abs/2504.06265

AdsMT is finally out in @NatureComms 🥳 It is designed for rapid prediction of global minimum adsorption energy (GMAE) from surface graphs and adsorbate descriptors. Thanks to @XuHuang461675 , @pschwllr and @NCCR_Catalysis! Paper & code: nature.com/articles/s4146… @SchwallerGroup

Announcing Neo-1: the world’s most advanced atomistic foundation model, unifying structure prediction and all-atom de novo generation for the first time - to decode and design the structure of life 🧵(1/10)

LLMs are pretty bad at writing molecules, but quite good at analyzing mols and reactions! In our new work we use LLMs+search in chemical tasks, unlocking steerable synth. planning and mechanism prediction 🌟 1/ @TheoNeukomm @d_armstr @ZJoncev @pschwllr arxiv.org/abs/2503.08537

🚨 Check out DrugFlow, our new generative model for structure-based drug design. DrugFlow provides an atom-level confidence score for each designed molecule, and can adjust molecular size on the fly! Additional details in thread 🧵 #ICLR2025

The code & camera-ready version of our #ICLR2025 paper on "Multi-domain Distribution Learning for De Novo Drug Design" are now available 📚 Paper: openreview.net/forum?id=g3VCI… 💻 Code: github.com/LPDI-EPFL/Drug… (1/4)

🎉Our BoLudo paper is in @J_A_C_S! Bayesian Optimization for nanocrystaL strUcture Design Optimization (jk, it's BOjana & LUDO😂) We show you can optimize ANYTHING when put on the right scale - even nanocrystals with surface energy! Also we discovered a new Cu shape! See how👇

Our paper on computational design of chemically induced protein interactions is out in @Nature. Big thanks to all co-authors, especially Anthony Marchand, @St_Buckley and @befcorreia nature.com/articles/s4158…