Austin Tripp @austinjtripp.bsky.social · 25/06/2025(I wrote this because this was something I inferred over time, and I think it's helpful to new reviewers to explain acceptance criteria more explicitly) 000
Austin Tripp @austinjtripp.bsky.social · 25/06/2025That is, a paper should provide either a unique result or a unique idea (ideally both), and on top of that should have no correctness issues. Full post is here: www.austintripp.ca/blog/2025-06... Happy to hear comments/feedback! I know my approach is just 1 of many! 100
Austin Tripp @austinjtripp.bsky.social · 25/06/2025NeurIPS 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) [...] 130
Reposted by Austin TrippValence Labs @valenceai.bsky.social · 20/05/20251/ 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 🧵 2136
Austin Tripp @austinjtripp.bsky.social · 16/05/2025If none of this makes any sense to you but you think multi-objective optimization is relevant, check out my full post below (where I explain MOO in more detail too). Bonus: also has an interactive visualization (kudos to Claude 3.7) www.austintripp.ca/blog/2025-05...austintripp.caChebyshev Scalarization ExplainedI've been reading about multi-objective optimization recently.1 Many papers state limitations of "linear scalarization" approaches, mainly that it might not be able to represent all Pareto-optimal sol 000
Austin Tripp @austinjtripp.bsky.social · 16/05/20252. Unfortunately, maximizing the Chebyshev objective may produce points which are *not* Pareto optimal (so some filtering might be required) ... 100
Austin Tripp @austinjtripp.bsky.social · 16/05/2025For 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) ... 110
Reposted by Austin TrippValence Labs @valenceai.bsky.social · 13/05/2025(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... 111
Austin Tripp @austinjtripp.bsky.social · 24/04/2025Really 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). 061
Austin Tripp @austinjtripp.bsky.social · 14/04/2025Claude 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...austintripp.caCoding python packages with AII tried using some new LLM tools to code 2 entire python packages (instead of editing a handful of lines at a time, which is what I did previously). It went well! These tools are not perfect, but they 120
Austin Tripp @austinjtripp.bsky.social · 14/02/2025(also, with ICML reviewing starting, this post will probably be the first in a series of posts about peer reviewing, stay tuned! 👀) 000
Austin Tripp @austinjtripp.bsky.social · 14/02/2025I wrote a blog post explaining this in more detail: www.austintripp.ca/blog/2025-02... If you think I'm wrong, I'd genuinely like to hear why. Please comment in 🧵austintripp.caIs offline model-based optimization a realistic problem? (I'm not convThis is a "quickpost": a post which I have tried to write quickly, without very much editing/polishing. For more details on quickposts, see this blog post. Offline model-based optimization (OMBO in 110
Austin Tripp @austinjtripp.bsky.social · 14/02/2025Can 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? 😂 110
Reposted by Austin TrippMaike Osborne @maosbot.bsky.social · 07/02/2025People who are masking are smart for two reasons: 1. They do not want to get brain damage 2. They are not getting brain damage 317028
Austin Tripp @austinjtripp.bsky.social · 31/01/2025Second note: there are a lot of more standard topics too, eg AI for science stuff, I'm just not posting that here. 000
Austin Tripp @austinjtripp.bsky.social · 31/01/2025Also funny: - Position: ML researchers should try to ensure their code is not a heaping pile of dogsh*t - Position: ML researchers should learn basic math (I'm talking to you, people who don't add error bars to their plots!!) - Position: focusing on meaningless benchmarks is stupid 010
Austin Tripp @austinjtripp.bsky.social · 31/01/2025Other abstracts: - Position: what if we started holding ML papers to actual standards? - Position: reviewers should actually read the papers they are reviewing - Position: reviewers should *at least try* to judge whether paper's claims are true before accepting them 000
Austin Tripp @austinjtripp.bsky.social · 31/01/2025(Note: titles are summarized/anonymized since I don't think I'm allowed to share) 000
Austin Tripp @austinjtripp.bsky.social · 31/01/2025My 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? 😶 430
Austin Tripp @austinjtripp.bsky.social · 26/01/2025Easy to get started on the antiviral challenge! I plan to submit some GP baselines from my PhD work (possibly with a collaborator). 051
Reposted by Austin TrippPolaris @polarishub.io · 14/01/2025🏁 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. 🧑💻 1176
Austin Tripp @austinjtripp.bsky.social · 13/01/2025My 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...github.comGitHub - AustinT/phd-thesis: LaTeX code for my PhD thesis (https://doi.org/10.17863/CAM.114023)LaTeX code for my PhD thesis (https://doi.org/10.17863/CAM.114023) - AustinT/phd-thesis 0182
Austin Tripp @austinjtripp.bsky.social · 10/01/2025Slightly longer version of this post is on my blog: www.austintripp.ca/blog/2025-01...austintripp.caWhat ML researchers and users get wrong: optimistic assumptionsML is often done poorly, both by "ML experts" (by which I mean people who understand the algorithms but not the data) and "ML users" (by which I mean people who understand their data, but not the algo 000
Austin Tripp @austinjtripp.bsky.social · 10/01/2025A 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! 1194
Reposted by Austin TrippPolaris @polarishub.io · 18/12/2024📊 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... 151
Austin Tripp @austinjtripp.bsky.social · 15/12/2024Valence is a great place to work- come find me at NeurIPS today if you want to learn more! 030
Austin Tripp @austinjtripp.bsky.social · 06/12/2024This looks like a really cool competition for small molecule property prediction in both 3D and 2D- great opportunity to work with real data 🚀 150
Austin Tripp @austinjtripp.bsky.social · 03/12/2024Finally, I'll be at the Recursion/Valence/NVIDIA social on Thursday Dec 12. See you there! 000
Austin Tripp @austinjtripp.bsky.social · 03/12/2024**Early-career researchers**: with the obvious caveat that I am still relatively junior myself, I'm happy to talk about applications, research directions, industry vs academia. I'm especially interested in helping anyone from an underrepresented background. 100
Austin Tripp @austinjtripp.bsky.social · 03/12/2024**BO/AL**: part of what's exciting about Recursion/Valence is the possibility of deploying BO/AL techniques at scale for real-world drug discovery tasks. We are always happy to collaborate with academics. Please reach out if you have research which you believe could be relevant 😀 100
Austin Tripp @austinjtripp.bsky.social · 03/12/2024**PhD internships**: even though only 1 internship is advertised now, Valence is always looking for talented interns. Topics can be anything with relevance to drug discovery, and usually result in a publication. I would be excited to work with an intern on BO/AL projects in particular! 100
Austin Tripp @austinjtripp.bsky.social · 03/12/2024I'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 180
Austin Tripp @austinjtripp.bsky.social · 03/12/2024I dislike reading “baby bird” responses to my reviews, especially since they usually don’t respond to my comments in a meaningful way. I try to be a bit more direct. 040
Reposted by Austin TrippValence Labs @valenceai.bsky.social · 27/11/2024Valence 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👇lu.maA Night of Science with Recursion, Valence Labs, and NVIDIA @ NeurIPS 2024 · LumaRecursion, Valence Labs, and NVIDIA is thrilled to extend an invitation to researchers, professors, investors, founders, students, and others interested in… 1157
Reposted by Austin TrippDerek Lowe @dereklowe.bsky.social · 26/11/2024The long and ugly story of Cassava Sciences’ supposed Alzheimer’s drug simufilam is finally over. It should have ended well before this.science.orgThe Cassava Saga Finally Ends 210432
Austin Tripp @austinjtripp.bsky.social · 22/11/2024Great quick blog post to understand benchmarks in drug discovery. My take: static datasets are probably not enough to prototype algorithms for discovery ‼️ 071
Reposted by Austin TrippCharlie Harris @harrisbio.bsky.social · 21/11/2024Now 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... 2256
Austin Tripp @austinjtripp.bsky.social · 18/11/2024Hey, I’d love to be added. I do ML for drug discovery at Recursion/Valence labs 010