Great collaboration with Keith Butler Dan Davis Aron Here is our @nature review and perspective on #MachineLearning learning in chemical sciences! nature.com/articles/s4158… #compchem

First ChemRxiv paper in our group! Get in touch if this work is relevant/interesting to you.

Today I learned what a lustrum was after seeing it in the opening line of the abstract in pubs.acs.org/doi/abs/10.102….

Our new paper on building coarse-grained force-fields using neural networks trained using a force matching principle and physically motivated priors is online now: pubs.acs.org/doi/abs/10.102… #compchem

New blog post: "A Recipe for Training Neural Networks" karpathy.github.io/2019/04/25/rec… a collection of attempted advice for training neural nets with a focus on how to structure that process over time

Insilico Medicine University of Toronto Vector Institute Alex Zhavoronkov, PhD (aka Aleksandrs Zavoronkovs) Alan Aspuru-Guzik Nature Biotechnology Here's the whole paper and a schematic of what they achieved w/ a GAN #AI strategy. Designed, synthesized and validated (both in vivo and in vitro) a new drug, from scratch.

Inclusion of learning curves combined with training and prediction timings should become the new standard in #quantummachinelearning #quantum #machinelearning #COMPCHEM

[1903.07930] Recycling knowledge to explore materials: a connector theory approach arxiv.org/abs/1903.07930

Large-Scale Screening of Zeolite Structures for CO2 Membrane Separations pubs.acs.org/doi/10.1021/ja…

Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights arxiv.org/abs/1909.08565 #compchem

The impressive ML prediction of electron density on polypeptides (and more) is now out in the 2019 Chemical Science Hot Article Collection: doi.org/10.1039/C9SC02… We hope you will like it as much as we do.

Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning disq.us/t/3g6aaxz

...the finding appears to support the emerging hypothesis that parts of the brain operate at a “critical point”... quantamagazine.org/deep-learning-…

Revealing Energetics of Surface Oxygen Redox from Kinetic Fingerprint in Oxygen Electrocatalysis pubs.acs.org/doi/abs/10.102…

Advancing Drug Discovery via Artificial Intelligence cell.com/trends/pharmac…

A great article by Pascal Pernot, Bing Huang and Andreas Savin NCCR-MARVEL CNRS 🌍 Faculté des Sciences de Sorbonne Université Université Paris-Saclay Universität Basel - Impact of non-normal error distributions on the benchmarking and ranking of #quantum #machinelearning models - bit.ly/2EfGv4J #compchem

Cool stuff from Bing Huang and Anatole von Lilienfeld

Conceptual DFT for solid surface makes sense at finite electronic temperature only! arxiv.org/abs/2012.11259

Our account of all the amazing contributions! Up to 30 pages of academic prose and >400 select references! Our (w Bing Huang) review has been accepted for the upcoming thematic issue on ML at the atomic scale in Chemical Reviews #compchem arxiv.org/abs/2012.07502

Nice review by Bing Huang, Guido von Rudorff, and Anatole von Lilienfeld on just how important DFT is to the future of AI for molecules. Still so many open questions (especially in biophysics) but quantum chemistry is definitely a fundamental part of the equation! science.org/doi/10.1126/sc…