NeurIPS reviews are due in 1 week 😱 If it's your first time reviewing (or if you don't feel totally confident about accept/reject), I recently wrote a blog post where I explain how *I* approach reviewing. Essentially: accept = correct AND (result OR idea) [...]

1/ At Valence Labs, @recursionpharma.bsky.social's AI research engine, we’re focused on advancing drug discovery outcomes through cutting-edge computational methods Today, we're excited to share our vision for building virtual cells, guided by the predict-explain-discover framework 🧵

For anybody working on multi-objective optimization: I recently did a deep-dive on Chebyshev scalarization and wrote a blog post. Key findings: 1. Unlike linear scalarization, varying the weights of Chebyshev scalarization will find *all* points on the Pareto front (not just the convex part) ...

(1/3)The poster submission deadline for MoML 2025 has been extended to May 20th, 2025. Don’t miss an opportunity to share your work at this years conference. Submit here: portal.ml4dd.com/moml-2025-po...

Really interesting essay- disagreements about AI existential risk might *really* be disagreements about dual-use nature of future technologies (since this is the vector people think AI could cause extinction).

Claude and Gemini do a pretty good job at coding some niche python packages from just a prompt. Some editing required, but if you haven't tried it yet then I highly recommend! www.austintripp.ca/blog/2025-04...

Can anybody explain to me why so many ML papers study "offline model-based optimization"? This is essentially "1-shot optimization". My main concern is "are there 1-shot optimization problems in real life"? Papers mention "drug discovery (DD)" as an example, but 1-shot DD never happens, no? 😂

People who are masking are smart for two reasons: 1. They do not want to get brain damage 2. They are not getting brain damage

My bid screen for ICML position papers is basically: - "Position: ML conference peer review is sh*t" - "Position: Let's abolish conference reviewing" - "Position: C'mon ML reviewers, surely we can do better than *this*" Am I in a "review hate" echo chamber or is everybody else seeing this too? 😶

Easy to get started on the antiviral challenge! I plan to submit some GP baselines from my PhD work (possibly with a collaborator).

🏁 The antiviral challenge is live! 🏁 Ready to test your skills on new data? Hosted in partnership with @asapdiscovery.bsky.social and @omsf.io, we've prepared detailed notebooks showcasing how to format your data and submit your solutions. 🧑‍💻

My PhD thesis is finally online. Thanks @cambridgemlg.bsky.social for a wonderful 4.5 years learning about probabilistic ML 😍 Code: github.com/austint/phd-... Thesis DOI: doi.org/10.17863/CAM...

A common issue I see in ML, both from ML "experts" and "users", is overly optimistic assumptions. "experts" (people designing algs) usually assume the data is very simple "users" (people using algs) usually assume that algorithms are more robust than they really are Conclusion: always be careful!

📊 Imagining the Future of ML Evaluation in Drug Discovery Our recent paper discussed the limitations of static leaderboards—they never tell the full story. What if we had a better and easier way of evaluating methods? A vision for the future, in the latest blog 🧵 polarishub.io/blog/imagini...

Valence is a great place to work- come find me at NeurIPS today if you want to learn more!

This looks like a really cool competition for small molecule property prediction in both 3D and 2D- great opportunity to work with real data 🚀

I'm attending NeurIPS next week- reach out if you want to meet for ☕️ I'm particularly interested in meeting: 1. PhD students interested in internships at Valence 2. people working on Bayesian optimization / active learning 3. anyone in tech-bio 4. early-career researchers Details in 🧵 below

Valence Labs will be co-hosting a TechBio social with @recursionpharma.bsky.social and NVIDIA at #NeurIPS in Vancouver. Join us on Thurs, Dec 12th. RSVP here: lu.ma/biikt7ox Our team will also be at NeurIPS throughout the week. See below for a summary of our papers👇

The long and ugly story of Cassava Sciences’ supposed Alzheimer’s drug simufilam is finally over. It should have ended well before this.

Great quick blog post to understand benchmarks in drug discovery. My take: static datasets are probably not enough to prototype algorithms for discovery ‼️

Now I can share external links without the posts being down regulated - I thought it would share this again!:) I have compiled a list of now 100+ companies in the 'TechBio' space into a fully open database for the community. Find here and please share if you like open.substack.com/pub/harrisbi...