Frank Noe
@FrankNoeBerlin
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9,714
Following
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266
Statuses
4,502
Scientist, #MachineLearning and #AI for the Sciences (esp. Physics/Chemistry). Scuba Diver and Traveler.
Berlin, Germany
Joined June 2017
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Tweeps - news! I'll join
@MSFTResearch
as research manager starting Oct 1st, opening a new AI4Science Lab in beautiful Berlin! We'll focus on fundamental challenges between
#MachineLearning
&
#Physics
/
#Chemistry
. We'll start at Alexanderplatz, and we'll hire at all levels! 🧵
As we advance Microsoft Research's AI4Science initiative, we’re opening a lab in Berlin. Learn more from Chris Bishop, Technical Fellow & Director, & Frank Noé, our new Partner Research Manager, as they discuss the fifth paradigm of scientific discovery.
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I made my introduction to
#DeepLearning
lectures (lots of references to shallow
#MachineLearning
and
#Physics
) public.
Hopefully useful for newbies who want to get an overview of methods before specializing on state-of-the-art stuff. Feel free to use!
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Wohoo - PauliNet, our deep
#NeuralNetwork
solution of the electronic Schrödinger equation is out in
@NatureChemistry
. Huge respect for
@jhrmnn
and Zeno Schätzle for championing this. Deep Quantum Monte Carlo is the future!
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German future prize for Sahin, Türeci, Kariko and Huber for developing the first approved Covid-19 vaccine and bringing the m-RNA technology to scale with
@BioNTech_Group
. I couldn't think of anything more appropriate. Huge congrats and thank you!
#zukunftspreis
@kkariko
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Folks we need a lockdown to contain this. Everyone off their computers for a month.
The number of monthly new ML +AI papers at arXiv seems to grow exponentially, with a doubling rate of 23months.
Probably will lead to problems for publishing in these fields, at some point.
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Excited to join
@MSFTResearch
on this journey. Big shoutout to Chris Bishop,
@sebnowozin
,
@wellingmax
,
@vdbergrianne
,
@mmjb86
,
@MaziarzKris
,
@marwinsegler
, Becky Frost and the whole team for being super welcoming and amazing.
Microsoft Research welcomes Visiting Researcher, Prof Frank Noé (
@FrankNoeBerlin
), a leading expert in machine learning for the natural sciences.
Learn more about opportunities across our global labs.
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It's finally here: the DeepTime software library!!!
Massive work led by Moritz Hoffmann, with Martin Scherer,
@tmhmpl
,
@andreasmardt
, Brian de Silva,
@brookehus
, Stefan Klus, Hao Wu, Nathan Kutz and
@eigensteve
.
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Let's celebrate this seminal paper by Katalin Karikó
@kkariko
. Describes how mRNA can be modified so that it doesn't cause an immune reaction. This is the basis for mRNA to be used in the Covid-19 vaccines of
@BioNTech_Group
,
@moderna_tx
and
@CureVacRNA
.
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Stochastic Normalizing Flows: We can train normalizing flows by combining invertible networks and stochastic dynamics (MCMC, Langevin) in any order. Better expressivity and sampling than either one.
With
@jonkhler
& Hao Wu
#MachineLearning
#DeepLearning
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Unbelievable to be elected to the Berlin-Brandenburg academy of sciences with these outstanding folks. Founded w/ Leibniz in 1700, Einstein revealed general relativity here in 1915. Now in good company with
@GroupParrinello
@c_drosten
@e__charpentier
...🤯
@bbaw_de
@FU_Berlin
Wir begrüßen unsere neuen
#Akademiemitglied
|er: Antje Boetius
@AWI_de
, Christian Drosten
@ChariteBerlin
, Eva Geulen
@zflkomm
, Volker Markl
@TUBerlin
/
@DFKI
, Frank Noé
@FU_Berlin
, Dagmar Schäfer
@MPIWG
, Matthias Warstat
@FU_Berlin
#Einsteintag
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15 PhD positions available on
#MachineLearning
for
#drugdiscovery
in EU grad school. Apply to project ESR15 to work with me at
@FU_Berlin
/ Germany and Ola Engkvist
@AstraZeneca
/ Sweden on deep learning for protein simulation.
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Who wants to come to Berlin and work with
@jhrmnn
and myself on the next generation of deep learning systems for Quantum Chemistry, especially deep QMC, exploiting ideas from Stat Mech, generative deep learning, equivariant graph nets etc? Send Email or DM.
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Learning coarse-grained molecular dynamics with graph neural networks. Led by
@brookehus
, Nick Charron and
@CecClementi
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Just read this. Beautiful and elegant method for computing chemical potentials by
@ChengBingqing
. This is the first time that a grand-canonical "simulation method" makes sense to me - by simply avoiding to do the simulation grand-canonical at all.
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Proud of our 2019
#MachineLearning
work. Highlights:
#BoltzmannGenerators
: Unbiased sampling of target distributions
PauliNet: Solving electronic Schrödinger equation
CGnet: Learn coarse-grained MD
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Can you believe it, I have been staring at protein structures for nearly 20 years but just ran the first gel in my life. The luxury of being a computer guy.
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2020 won't be less exciting. My personal/private highlights:
-
@CecClementi
will move to Berlin as an Einstein professor for physics
- We are buying an apartment in Schöneberg
- We are getting married!!
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Antisymmetry is what makes electronic structure calculations hard. We need more
#MachineLearning
work to make progress with this fundamental problem. Stefan Klus takes a stab at it by developing antisymmetric kernels:
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We propose a new+data-efficient way for
#MachineLearning
coarse-grained molecular force fields from simulation data (e.g. all-atom). With
@jonkhler
,
@__kraemer__
, Yaoyi Chen,
@CecClementi
.
@bifoldberlin
@MSFTResearch
@ERC_Research
@FU_Berlin
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Online workshop on protein dynamics coming up April 26-28. Awesome speakers including
@RommieAmaro
@LindorffLarsen
@gdefabritiis
@CarloCamilloni
@CecClementi
and many folks not on twitter ;-) Registration required.
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A bright moment in dire times.
@CecClementi
being appointed Einstein professor for physics in Berlin by FU president Günter Ziegler (with safety distance).
@Einstein_Berlin
,
@FU_Berlin
.
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Internship opportunity at
@MSFTResearch
#AI4Science
on generative protein models. Location Berlin, Amsterdam or Cambridge.
Apply here asap:
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First official release of the DeepQMC code for Quantum Monte Carlo with
#NeuralNetworks
wave functions, including architectures like PauliNet, FermiNet and DeepErwin. By Zeno Schätzle,
@PBerntSzab1
, Matej Mezera and
@jhrmnn
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#MachineLearning
coarse-grained molecular dynamics with flow-matching is now out in JCTC
@JCIM_JCTC
!
@jonkhler
Yaoyi Chen (not on Twitter?)
@__kraemer__
@CecClementi
.
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Tweeps at
#NeurIPS2022
#ML4PS2022
@lrml_bio
@AI_for_Science
looking for exciting jobs in deep learning and molecular sciences?
@MSFTResearch
AI4Science is hiring in Berlin and other sites. DM me or approach my colleagues for more info.
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Hi Tweeps: Doing a Markov Modeling / Time Series Analysis Zoom tutorial using DeepTime and PyEMMA on Feb 21-24. We will schedule everything from noon to 5 pm CET so that at least US east-costers have a chance as well!
20 spots. Please register - see:
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LinkedIn keeps suggesting I should apply for our jobs at
@MSFTResearch
AI4Science Berlin, and I am tempted to…
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2006 PhD
2012 Scuba diver
2013 Professor
2021 Married love of my life
2022 First real job
Seems like a weird order I know
2006: semi-prof reggae band
2008: politics & economics
2009: pure math
2011: major depression
2012: art school
2013: 20h/w webdev
2016: bsc applied cs
2017: married
2018: msc AI
2018: start PhD in ML+Physics
2020: beat depression
2021: DeepMind internship
2023: first real job
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Microsoft research announces AI4Science initiative focusing on next generation
#MachineLearning
for natural sciences. Super exciting!
Microsoft Research announces AI4Science, a new global team of machine learning, quantum physics, computational chemistry, molecular biology, fluid dynamics, and software engineering experts working to tackle important societal challenges. Learn more:
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Hao Wu has developed a very nice approach to compute reaction coordinates of molecules with normalizing flows by leveraging the idea that in reaction coordinate space the system's time propagation should follow a simple dynamical law.
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I have a proposal. How about removing any occurrences of
#MachineLearning
and
#ArtificialIntelligence
from paper and workshop names as it’s trivially an ingredient in pretty much everything now?
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Sometimes it just fits. Within the same 15 mins, I made a postdoc offer, got a positive response and received news that a EU grant will be funded :-)
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Tweeps - apply here for senior researcher and engineering positions in
@MSFTResearch
AI4Science Berlin! We'll keep these open for a few more weeks.
If you have already applied please give us some time to respond.
Tweeps - news! I'll join
@MSFTResearch
as research manager starting Oct 1st, opening a new AI4Science Lab in beautiful Berlin! We'll focus on fundamental challenges between
#MachineLearning
&
#Physics
/
#Chemistry
. We'll start at Alexanderplatz, and we'll hire at all levels! 🧵
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76
867
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Awesome
@CecClementi
giving a honorary speech in the Italian embassy Berlin on the occasion of the international women's day. 💪👩🔬❤💥
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I am so happy to see this. A big round of applause to the team for this heroic effort!!!
🚨ANNOUNCEMENT🚨
The
@covid_moonshot
is now published in
@ScienceMagazine
! The paper reflects the major contributions of the FAH community and a global network of scientists collaborating to make drug discovery open, globally accessible, and affordable
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Exciting: excited PauliNet - computing excited states of electronic Schrödinger equation w. deep neural nets + Quantum MC. By M. Entwistle, Z. Schätzle, P. Erdman and
@jhrmnn
#MachineLearning
#quantum
@FU_Berlin
@bifoldberlin
@MSFTResearch
@ERC_Research
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We are setting up an
#AI
/
#MachineLearning
-driven protein design platform. Looking for a highly motivated PostDoc with experience in protein purification and/or RNA biology. Ideal: experience with experimental protein design. Collab with Daumke (MDC) and Schacherl (Charite).
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Cool paper on transition-path sampling with Boltzmann-Generator moves by Michael Plainer,
@guennemann
@_bunnech
@HannesStaerk
:
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Woohoo, Stochastic Normalizing Flows coming up as a
#NeurIPS2020
spotlight talk. Thanks 10^6 to Hao Wu and
@jonkhler
.
P.S. Arxiv version is identical in methods and results. That version was rejected from ICML. Except a few improvements for camera ready!
Stochastic Normalizing Flows: We can train normalizing flows by combining invertible networks and stochastic dynamics (MCMC, Langevin) in any order. Better expressivity and sampling than either one.
With
@jonkhler
& Hao Wu
#MachineLearning
#DeepLearning
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Congrats to Yaoyi Chen to his first first-author paper on Machine Learning implicit solvation via the multiscale coarse-graining approach:
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Just out in
@NatureComms
: Excited states calculation with deep quantum Monte Carlo by Mike Entwistle, Zeno Schätzle,
@PBerntSzab1
,
@jhrmnn
.
#MachineLearning
@MSFTResearch
@FU_Berlin
@ERC_Research
@dfg_public
@MATHplusBerlin
@bifoldberlin
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Excited: first joint paper with Klaus-Robert Müller, Alex Tkatchenko and
@CecClementi
, coming up as an Annual Review in Physical Chemistry.
First strike in our efforts to unite Machine Learning for Quantum and Statistical Mechanics
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Roadmap on
#MachineLearning
in Electronic Structure: Perspectives on current + future challenges on predicting material properties, learning force-fields, solution of the many-body problem etc.
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Pls Share: Wanna do a
#MachineLearning
PhD in Europe? Any core ML discipline or ML + Phys / Chem / Bio?
Apply to
@ELLISforEurope
here by Dec 1st. Work with two top Labs/PIs of your choice.
My group has openings, please contact for more info.
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Super interesting work by Falkner, Coretti, Romano, Geissler (RIP Phil) and Dellago: They show how Boltzmann Generators can be extended to help sampling transition path ensembles efficiently.
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Our deep learning approach to identify independent Markov domains in molecules is out in
@NatureComms
.
@andreasmardt
@tmhmpl
@CecClementi
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96
Working towards computing kinetics for large biomolecules with independent Markov decomposition.
@tmhmpl
championed this work, big shoutout to the team Mauricio del Razo,
@CTLeeRes
@RommieAmaro
@biobryn
.
So happy to have a paper with you Rommie!
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There are still honest people in the 🌎.
Lost my backpack with credit cards, IDs, IPad in the chaos of moving with a shared car. Finder researched me and gave it back. Super Happy.
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Join us for on a wonderful postdoc position at
@MSFTResearch
AI4Science Berlin on
#MachineLearning
for Molecules!
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Tweeps, wish you all an awesome, healthy and happy new year! Hope you and your dear ones stay safe, you get rewarded for your hard work, your grants and startups get funded, your AIs get a little smarter.
And don't overdo it with resolutions. Eating is a good thing! Buon Anno!!
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Interested in participating in an online tutorial on Markov modeling and using the deeptime + PyEMMA software packages on March 1-3? There are still spots available - please register by Email (see link).
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The protein TMPRSS2 is a great COVID-19 drug target, but we have no experimental structure. Here we provide the as-yet most advanced equilibrium structure model and study how two drug candidates, camostat and nafamostat work.
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This one was very tough, and it's finally out! In-depth analysis of ubiquitin-SH3 protein-protein binding mechanism combining extensive MD, Markov modeling and NMR with
@smnlssn
, Kalyan Chakrabarti, Christian Griesinger, Thomas Weikl and many colleagues
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Welcoming postdoc openings for
#MachineLearning
in Statistical Physics and/or
#quantum
Physics / Chemistry. Pls Email frank.noe
@fu
-berlin.de or DM with CV+publications+1-2 refs.
#postdocposition
#AcademicTwitter
@jhrmnn
@CecClementi
@bifoldberlin
@FU_Berlin
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Code for PauliNet - deep neural network solution of the electronic Schrödinger equation in open-source deepqmc👇
Paper: , Talk:
#MachineLearning
@ELLISforEurope
@jhrmnn
#QuantumMechanics
@MATHplusBerlin
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As someone loving
#MachineLearning
and Physics/Chemistry, I am overwhelmed by
#NeurIPS2020
having 5 exciting workshops on this interface. We are not writing papers that fast...
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Opening for PhD positions in
#MachineLearning
#ArtificialInteligence
at ELIZA/
@ELLISforEurope
Berlin. Various research and application areas are possible :-) Apply by Dec 8.
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@andreasmardt
&
@tmhmpl
have developed the
#MachineLearning
approach iVAMPnet: decompose macromolecules into dynamically independent subunits & describe each by a Markov State Model. With
@CecClementi
. 🧵⬇️
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This
@ipam_ucla
workshop on learning and emergence in molecular systems was really spectacular and a lot of fun!
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New work led by Yaoyi Chen:
#MachineLearning
implicit solvation for molecular dynamics using the coarse-graining principle and CGnet.
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Fantastic work by my
@MSFTResearch
AI4Science colleagues.
#GenerativeAI
for Materials is going to be a gamechanger, and this is only the beginning.
[1/N] Generative AI has revolutionized how we create text and images. How about designing novel materials? We at
@MSFTResearch
#AI4Science
are thrilled to announce MatterGen: our generative model that enables broad property-guided materials design.
👇
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Wonderful work led by
@MohsenSadeghi
on the coarse-grained simulation of biomembranes with incorporating hydrodynamics, realistic kinetics and long timesteps. This is meant to be used in particle-based reaction-diffusion simulations of cells:
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Excited to share our approach for
#machinelearning
path-integral molecular dynamics to account for quantum nuclear effects in spectra and other observables. Fantastic team led by
@venkatkapil24
@CecClementi
@FelixMusil
.
An attempt towards
#pathintegral
quantum dynamics via classical molecular dynamics with
#machinelearning
and coase-graining alla
@FelixMusil
@CecClementi
@FrankNoeBerlin
. Feedback welcome. :) Thanks
@snsf_ch
@ChemCambridge
@ChurchillCol
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My slides on deep learning for many-body physics problems from the talks at Perimeter and Vector AI institute:
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Interested in a PhD on the interface of
#machinelearning
and biology/biophysics/comp chem? This is a good opportunity and allows us to admit both students with Bachelor and Master degrees on separate tracks:
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@leonklein26
introduces flow matching with equivariance. This allows us for the first time to get flows working for iid sampling of molecular structures in Cartesian coordinates in such a way that we can get reasonable Monte Carlo acceptance rates.
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Me trying to comprehend the lastest developments in deep Quantum Monte Carlo while preparing my overview talk.
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1/ IMHO
@nature
's guided OA pilot is misguided. While it's optional now, a scenario in which researchers need to pay upfront to get reviews is unethical. Don't go there
@NaturePhysics
@NatureComms
@NatureChemistry
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@adad8m
On the risk of getting yelled at, but I would do this in <5 min with PowerPoint. Takes some practice but is super efficient for these things when you know how.
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Our paper on discovery of a new state across the bromodomain superfamily is out in
@PNASNews
work led by Lluis Raich and
@smnlssn
, super grateful to the fantastic team and support of
@ClaraDChrist
@Bayer
@MATHplusBerlin
@FU_Berlin
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Happy to share our MLST paper on symmetric and antisymmetric kernels for
#MachineLearning
problems in physics and chemistry. Just out
@bifoldberlin
@MATHplusBerlin
@FU_Berlin
@ERC_Research
'Symmetric and antisymmetric kernels for
#machinelearning
problems in
#quantum
#physics
and
#chemistry
' by
@FrankNoeBerlin
S Klus, P Gelß and F Nüske
@FU_Berlin
@UniOfSurrey
@unipb
@RiceUniversity
hits 500 downloads already!
#compchem
#opendata
#compphys
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Immense pleasure to having worked with this team and finally see this out. Using
#MachineLearning
, the first CG forcefield that predicts free energy landscapes similar to all-atom for unseen proteins, and it's much faster than all-atom. Tour-de-force by
@CecClementi
+team
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Very happy and grateful that Chemistry at
@RiceUniversity
has renewed my adjunct appointment. Looking forward to come back and visit when the Covid situation allows us.
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I am working on an optimization joke, but it's not converging...
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Ho ho ho, now I a have a machine ... actually it's a camera :-) Thanks to
@CecClementi
I have a wonderful new scuba toy - can't wait to try it out 🐠🐟🐡🐬🦈📸
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Wanna do a PhD in the mathematical sciences in Berlin? Machine Learners and Natural Scientists with a strong math inclination welcome. Apply here:
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Welcome new lab mate
@SherryLixueC
joining today as a researcher in
@MSFTResearch
AI4Science. Looking forward to working with you on the frontier of AI for quantum Chemistry.
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A beautiful explanation of key ideas of the BioNTec vaccine for computer scientists
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Most downloaded articles in Annual Reviews 2020 includes our review on ML for molecular simulation with
@CecClementi
, Aleks Tkatchenko and Klaus Müller. It's free for download temporarily here (also on arXiv):
@AnnualReviews
@bifoldberlin
2
9
68
Marvelous day with the
@CecClementi
and Noe groups and we managed to sway the weather into admitting a BBQ. A few people were missing but now we have a nearly complete group shot that is photoshoppable to perfection.
0
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Excited to speak at the AI4Science kickoff workshop of our
@ELLISforEurope
colleagues in Amsterdam tomorrow. Event starts at 9am CET:
@wellingmax
,
@BerndEnsing
,
@marcelworring
,
@KyleCranmer
,
@gdefabritiis
,
@cosmo_shirley
,
#MachineLearning
2
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68
We propose temperature-steerable flows that learn a family of probability distributions parametrized by temperature. Allows to use flows in combination with parallel tempering simulation for sampling. Led by Manuel Dibak and Leon Klein.
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Opening at
@FU_Berlin
for a three-year postdoc position for
#MachineLearning
in the molecular sciences. Candidates with strong theory and method development knowledge in Quantum Chemistry or Statistical Mechanics are particularly encouraged to apply.
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We are building a sklearn-style
#MachineLearning
framework for dynamical models from time series data: MSMs, (E)DMD, VAMP, Sindy, kernel&deep versions of those. Led by M. Hoffmann w.
@eigensteve
,
@brookehus
,N. Kutz,S. Klus & everyone invited!! What's your favorite package name?
sktime / scikit-time
80
skdyn / scikit-dyn
125
dynamo (dynamical model)
95
cyberdyne
49
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We live in a time of crises and uncertainty, but also a time where science has shown to have profound and direct impact on the course of events. I want to dedicate the 2nd half of my career to be part of this, developing key technologies and scaling them to real-world relevance.
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New version of excited PauliNet -- a deep Quantum Monte Carlo approach to compute ground and excited states of the electronic Schrödinger equation is online. Now including conical intersections!
Exciting: excited PauliNet - computing excited states of electronic Schrödinger equation w. deep neural nets + Quantum MC. By M. Entwistle, Z. Schätzle, P. Erdman and
@jhrmnn
#MachineLearning
#quantum
@FU_Berlin
@bifoldberlin
@MSFTResearch
@ERC_Research
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Moritz Hoffmann figured out a way to generate valid Euclidean distance matrices without going through the 3D representation. We believe this may be a very useful tool when generating molecules or other particle data.
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