I’ve reviewed TabPFN in the past. https://macinchem.org/2025/02/06/looking-at-tabpfn and I noticed there was a recent update. TabPFN is a foundation model trained on around 130,000,000 synthetically generated
Tag: machine learning
OpenADMET have just announced the ExpansionRx-OpenADMET blind challenge in partnership with Expansion Therapeutics. Expansion Therapeutics have decided to make all the ADMET publicly available. “We
TabPFN is a foundation model trained on around 130,000,000 synthetically generated datasets that mimic “real world” tabular data. These datasets sampled dataset size and number
A recent paper published in Nature caught my eye, Accurate predictions on small data with a tabular foundation model by Hollmann et al., Here we present
A really interesting preprint caught my attention from Connor Coley’s group at MIT. ShEPhERD diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design https://arxiv.org/abs/2411.04130v1 …
A new Apple preprint has appeared on Arxiv. https://arxiv.org/pdf/2403.20329.pdf Reference resolution is an important problem, one that is essential to understand and success- fully handle
I suspect many people have been anticipating this, whilst AlphaFold was a great step forward in predicting protein 3D structure it did have significant limitations.
I know a few folks have been using this, good to see this publication DOI. Chemprop implements the D-MPNN architecture and offers simple, easy, and
We are starting to see papers coming from Apple that highlight their efforts in the machine learning/artificial intelligence area. Recently we have seen MLX a