Sebastian Ober

We're hiring! The AI and Data Analytics (AIDA) team in Mayo Clinic Radiation Oncology is recruiting Research Fellows to advance machine learning for real-world clinical impact. 🧵

Machine Learning Scientist Job Opening: Machine Learning Scientist at BigHat Biosciences in San Mateo, CA.

We're hiring for an ML Scientist at BigHat Biosciences to work on advancing state-of-the-art ML methods with direct application to designing real-world antibodies! I've loved working here so far; feel free to DM with any questions.

bighatbiosciences.pinpointhq.com/en/postings/...

GitHub - 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

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...

apply it to regression - but I agree that pretty much reduces to what you did!

Thanks to the pointer on the log det and trace approxes. I'll definitely have a look! (2/2)

Yeah pretty much! I'm not entirely sure how I see how it's an approximation of H[Y_1, ..., Y_B | X_1, ..., X_B] - could you clarify?

I agree it doesn't take into account aleatoric uncertainty - but that's kind of the point imo! My focus here was really on classification, although you can ... (1/2)

I'll also be presenting "Active learning for affinity prediction of antibodies" at both BDU and MLSB (tomorrow), work done with Alexandra Gessner, Owen Vickery, Dino Oglic, and Talip Ucar! openreview.net/pdf?id=rSnUP... (3/3)

This project was a lot of fun, but wouldn't have been possible without my great collaborators: @spmontecarlo.bsky.social, @tomdiethe.com, and Henry Moss.

Come to East Rooms 8/15 for the lightning talks (14:30-15:00) and poster session (15:00-16:00), but also for a great workshop! (2/3)

Excited to be presenting my work, "Big batch Bayesian active learning by considering predictive probabilities" at the Bayesian Decision Making & Uncertainty (BDU) Workshop @neuripsconf.bsky.social, as both a lightning talk and a poster!https://openreview.net/pdf?id=VikX9euujU (1/3)

📢 Excited to present our work at #NeurIPS2024!
📄 "Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood"
Read it here: arxiv.org/abs/2402.15978

Details in 🧵

Excited to be attending @neuripsconf.bsky.social from Wednesday! Reach out if you're interested in any of:
- ML for protein therapeutics
- Bayes opt/active learning
- GPs/BNNs/DGPs
Looking forward to catching up with old friends & meeting new ones! I'll also have workshop posters - more later!

Could you add me please? Doing ML for antibody therapeutics!

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