It’s a wrap! 🎉 Thanks to all speakers, organizers, and participants who made the AI4D3 @ NeurIPS2025 workshop a success. Photos + highlights👇 🔗 https://t.co/PMXlrBhARw

Our @NeurIPSConf workshop ✨AI Virtual Cells & Instruments✨ has a superstar lineup of roundtable discussions! 🛠️Building AI Virtual Cells & Instruments 💊Lessons Learned: AI-first Drug Discovery & Development Join us on Dec 6 @ San Diego Convention Center Upper Level Rm 28A-E!

(4/6) The invited speakers are @biogerontology (Insilico Medicine), Tommi S. Jaakkola (MIT), Rick L. Stevens (UChicago & Argonne NL), @jinboxu_chicago (TTIC & Molecule Mind), @ericxing (MBZUAI, GenBio, & CMU), @MengdiWang10 (Princeton), and @LindaBGoodman (FaunaBio).

@biogerontology @jinboxu_chicago @ericxing @MengdiWang10 @LindaBGoodman (5/6) The organizers are @QuanquanGu (UCLA & ByteDance), @_michellemli (Harvard), @ChongLiuCS (UAlbany), @XuefengCS (UChicago), Abhishek Pandey (AbbVie), @tagasovska (Prescient Design - Genentech), and @marinkazitnik (Harvard).

(1/6) We’re thrilled 🎉 to launch the #NeurIPS2025 Workshop on AI Virtual Cells and Instruments: A New Era in Drug Discovery & Development (AI4D3-2025) in San Diego, CA on December 6 or 7!🥳 🔗Workshop site:

🔍 Call for Reviewers: AI4D3@NeurIPS 2025 We're seeking experts in AI & drug discovery to review submissions for our NeurIPS workshop. 🗓️ Deadline: May 30, 2025 📍 Workshop: Dec 2025, San Diego ✅ Sign up: https://t.co/VDZIKa6i2I #AI4D3 #NeurIPS2025 #DrugDiscovery #AI

Form to register your attendance and (optionally) talk/poster presentation: https://t.co/C7YyDgJfdq

Join us for an exciting workshop about cutting-edge AI for drug discovery and development on April 4, 2025, at University of Chicago 🙌 #AI4D3

#ICML2024 I will present Entropy-Reinforced Planning with Large Language Models for Drug Discovery poster! Come and chat if you are interested!! Hall C 4-9 #2410 Thu 25 Jul 1:30 p.m. CEST — 3 p.m. CEST Paper: https://t.co/76CZ55z8Px

Call for reviewers of 2nd Workshop on AI for Drug Discovery and Development @AI4D3 at @NeurIPSConf '24! Feel free to sign up and share! https://t.co/d62zbSe4LB

website:

It’s great to introduce <Blending IL and RL for Robust Policy Improvement> as a #SPOTLIGHT presentation at #ICLR2024 (joint work with @takuma_yoneda, Rick Stevens, @mattrwalter @yuxinch). Thanks to quite a few people who stopped by with interesting questions and follow-ups!

Happening Now! Excited to deliver an oral presentation at #NeurIPS23 AI for Drug Discovery workshop (AI4D3). 📜"DrugImprover: Utilizing Reinforcement Learning for Multi-Objective Alignment in Drug Optimization" 📍Room #242 ⏰ 1:20 p.m- 2:25 p.m. CST 🔗 https://t.co/A7CV7X9UeP

If you are attending #ICML2023, come by our poster on Tuesday at 11am @ Exhibit Hall 1 to have a chat! https://t.co/W4W9Ej0gcK

In particular, MAPS actively selects which of the oracles to imitate and improve their value function estimates, and MAPS-SE additionally leverages an active state exploration criterion to determine which state one should explore.

MAPS and MAPS-SE, which stand for Max-aggregation Active Policy Selection with Active State Exploration, are classes of policy improvement algorithms that perform imitation learning from multiple suboptimal oracles.

How can an agent actively learn from multiple blackbox oracles by taking advantage of their complementary expertise to learn a better policy in a sample-efficient manner? In our #ICML2023 paper, we introduce MAPS (Active Policy Selection) and MAPS-SE (+Active State Exploration)

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