@hbdft2008

Postdoc@unibas compchem, qml, conceptual DFT, electrochem

Joined July 2017
  • Tweets30
  • Following63
  • Followers52
Nice review by Bing Huang, @ferchault, and @ProfvLilienfeld 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/scie…

The central role of density functional theory in the AI age

Density functional theory (DFT) plays a pivotal role in chemical and materials science because of its relatively high predictive power, applicability, versatility, and computational efficiency. We...

science.org
3
27
1
87
11,097
Our account of all the amazing contributions! Up to 30 pages of academic prose and >400 select references! Our (w @hbdft2008) review has been accepted for the upcoming thematic issue on ML at the atomic scale in @ACSChemRev #compchem arxiv.org/abs/2012.07502
2
15
78
Cool stuff from @hbdft2008 and @ProfvLilienfeld
NCCR-MARVEL@nccr_marvel14 Sep 2020
Latest from @ProfvLilienfeld lab in @NatureChemistry describes "amon”-based #MachineLearning approach that excels in modelling quantum properties of a wide range of systems. More here: nccr-marvel.ch/highlights/20… @UniBasel_en
4
12
A great article by Pascal Pernot, Bing Huang and Andreas Savin @nccr_marvel @CNRS @ScienceSorbonne @UnivParisSaclay @UniBasel - Impact of non-normal error distributions on the benchmarking and ranking of #quantum #machinelearning models - bit.ly/2EfGv4J #compchem
2
3
8
Bing Huang retweeted
Eric Topol
@EricTopol2 Sep 2019
Replying to @EricTopol @InSilicoMeds @UofT @VectorInst @biogerontology @A_Aspuru_Guzik @NatureBiotech
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.
2
50
9
115
Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights arxiv.org/abs/1909.08565 #compchem
6
12
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/C9SC02696G We hope you will like it as much as we do.
COSMO Lab 🇨🇭🇪🇺@lab_COSMO2 Jul 2019
Replying to @lab_COSMO
We start with a *much* improved electron charge learning effort with the @corminboeuf_lab crew, within the @nccr_marvel. Spoiler alert: we can predict charge density on polypeptides. Find out more on chemrxiv.org/ndownloader/art…
2
9
39
Great collaboration with @keeeto2000 @danddavis @lonepair Here is our @nature review and perspective on #MachineLearning learning in chemical sciences! nature.com/articles/s41586-0… #compchem
10
39
First @ChemRxiv paper in our group! Get in touch if this work is relevant/interesting to you.
ChemRxiv@ChemRxiv2 Apr 2019
Towards a Design of Active Oxygen Evolution Catalysts: Insights from Automated Density Functional Theory Calculations and Machine Learning by Zachary Ulissi & co-workers bit.ly/2YCxN5Q #compchem #AIChemPreprints
4
24
Today I learned what a lustrum was after seeing it in the opening line of the abstract in pubs.acs.org/doi/abs/10.1021….

Outlining the Scaling-Based and Scaling-Free Optimization of Electrocatalysts

Abstract. For nearly 15 years, significant efforts have been directed toward the computational design of electrocatalysts for a variety of important reacti

pubs.acs.org
1
1
4
Bing Huang retweeted
Simon Olsson@smnlssn15 Apr 2019
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/10.1021… #compchem

Machine Learning of Coarse-Grained Molecular Dynamics Force Fields

Abstract. Atomistic or ab initio molecular dynamics simulations are widely used to predict thermodynamics and kinetics and relate them to molecular structu

pubs.acs.org
30
2
108
New blog post: "A Recipe for Training Neural Networks" karpathy.github.io/2019/04/2… a collection of attempted advice for training neural nets with a focus on how to structure that process over time
72
1,622
176
4,693
Inclusion of learning curves combined with training and prediction timings should become the new standard in #quantummachinelearning #quantum #machinelearning #COMPCHEM
Thomas Miller@tfmiller36 Sep 2019
Replying to @tfmiller3 @ProfvLilienfeld @MicheleCeriotti @A_Aspuru_Guzik @adrian_roitberg @olexandr @itamblyn @corminboeuf_lab @andrewwhite01 @waller_lab @teodorolaino @PaesaniLab @jppiquem
Timings also provided (Fig 8 of arXiv:1909.02041).
4
12
Dirk's magnum opus on Estimating Systematic Error and Uncertainty in Ab Initio Thermochemistry ... the ATOMIC(hc) Protocol pubs.acs.org/doi/abs/10.1021…
1
2
7
The QM9 challenge: Who will be the first to reach 1kcal/mol @ N=100? Prospective winners and panel members DM me! #MachineLearning #CompChem @olexandr @carlosevmoura @marquetand @A_Aspuru_Guzik @adrian_roitberg @janhjensen @vl_deringer @MicheleCeriotti @jppiquem @RolandLindh
7
31
3
84
Load more