David Layden @layden_variable
Quantum & ML. Staff research scientist @IBMResearch and coffee aficionado. Prev: PhD @MIT. Views are my own. Cambridge, MA Joined April 2010-
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🚨 Thrilled to be co-organizing a Simons Institute semester-long program on diffusions and flows with @joanbruna, Sinho Chewi, @KonstDaskalakis, @ArnaudDoucet1 in Fall '27! The call for Simons postdoctoral research fellowships for the program is out now, more info below ⬇️ 1/3
@zlatko_minev So can quantum error correction! nature.com/articles/s4153…
💯 text diffusion is the future 🚀
new blog post! I'm convinced text diffusion is the future, and we'll start to see it everywhere very soon. varunneal.github.io/essays/diffusi…
Wavefunction flows simulate diffusion models on a quantum computer. My first NeurIPS paper without experiments O_O congrats to @layden_variable @rndm_wlks @flashlemonade @anchowdhury13 arxiv.org/abs/2510.08462
Our new paper published in @ScienceMagazine "High-capacity associative memory in a quantum-optical spin glass." science.org/doi/10.1126/sc… arxiv.org/abs/2509.12202 (free version) In a large collaboration of very talented quantum optics theorists and experimentalists and theoretical neuroscientists, lead by Benjamin Lev, we realized and analyzed memory recall in a Hopfield associative memory where the neurons are made of atomic spins and the synapses are made of light exchanged by the spins in a cavity quantum electrodynamics system. Intriguingly the cavity quantum electrodynamics yields two distinct dynamical effects that enhance memory recall compared to the classical Hopfield model: 1) steepest descent rather than Glauber dynamics make memory basin sizes larger 2) coupling between atomic positions and spin orientations leads to a spin dependent change in synaptic connectivity that is a direct analog of short-term Hebbian synaptic plasticity, which again enhances memory. This is a precursor to learning in a quantum optical system.
🚨 We finally have a better understanding of how the different paradigms for discrete diffusion compare! In new work with Liye Wang, we prove a quadratic separation between the parallel generation capabilities of uniform and Gaussian diffusion relative to unmasking! 1/
Mathematician: Jacobian conjecture is false! After 87 years we've found one counter-example. Statistician: So you're telling me the Jacobian conjecture is true almost surely.
A friend just revealed to me that the middle name of Benoit B. Mandelbrot is Benoit B. Mandelbrot.
@Liv_Lanes Same. I live mostly off Spindrift, for the environment.
Population dynamics (eg murmuration of birds 🐦🐦🐦) is notoriously hard to learn; choosing the right model for the dynamics is even harder. In our #ICML2026 spotlight, we introduce Wasserstein Lagrangian Mechanics (WLM) for learning population dynamics from observations, which - Covers both first-order (gradient descent) and second-order dynamics (e.g. oscillations) - Allows learning more expressive dynamics (including complex interactions) with fewer assumptions - Generalizes in space (across different initial conditions) and time (beyond the training time snapshots) [1/n] 🧵
My first blog post in over a year is a deep dive on flow maps🗺️, or how to learn the integral of a diffusion model to enable faster sampling and several other cool tricks. It's the longest one yet👀 Let me know what you think! sander.ai/2026/05/06/flo…
The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing physics.mit.edu/?p=24365
Adopting Claude speak in my regular life, episode 1: Partner: Did you do the dishes tonight? Me: Yes they're done. Partner: Why are they still dirty? Me: You're right to push back. I didn't actually do them.
I've been talking a lot about the rehabilitation of continuous language diffusion recently, which seems to be in full swing. If you're curious to learn where things stand, read @FEijkelboom's blog post! (If flow maps remain a mystery to you, I may be able to help, stay tuned👀)
Flow-LLM Blogpost :D flow-based-llms.github.io In the last few weeks, a bunch of work on flows for language came out 🌊 That is exciting, because it makes truly parallel text generation feel real: generation where models can keep refining the whole response during inference,
Constraints are the catalyst of invention. An infinite search space leads to paralysis. The most creative inventions happen when you are forced to solve a problem within appropriately narrow constraints.
What if AI could invent enzymes that nature hasn’t seen? 👩🔬🧑🔬 Introducing 🪩 DISCO: Diffusion for Sequence-structure CO-design 14 rounds of directed evolution and over a year of wet lab work. That's what it took to engineer an enzyme for selective C(sp³)–H insertion, one of the most challenging transformations in organic chemistry. DISCO surpasses this with a single plate. No pre-specified catalytic residues, no template, no theozyme, no inverse folding, just joint diffusion over protein sequence and structure. 📝 Blog: disco-design.github.io 📄 Paper: arxiv.org/abs/2604.05181 💻 Code: github.com/DISCO-design/D…
@NandoDF It depends on the area of ML. For instance, diffusion/flow-based models turn out to be deeply linked to quantum computing (arXiv:2510.08462), which clearly wouldn't have been apparent in 2017. There have also been misc. other algorithmic advances, e.g., for MCMC.
"There is a single light of science, & to brighten it anywhere is to brighten it everywhere." — Isaac Asimov
Many of my colleagues and I attempted to apply diffusion- and flow-model reasoning to the Schrödinger equation, but we were all missing David in our equations! It started as casual chats where we'd explain concepts from our domains to each other. Until one day David just brought a solution that clicks immediately when you see it – "clearly, this is how it should be done." Absolutely beautiful in its simplicity and novelty! Don't get scared by all the rigorous analysis (and many months of David's work) that followed – take a peek at this connection between the continuity equation and the Schrödinger equation!
Flow and diffusion models are the Schrödinger equation in disguise. That’s what we show in our recent paper: "Wavefunction Flows: Efficient Quantum Simulation of Continuous Flow Models" arxiv.org/abs/2510.08462 This has important consequences in both ML and quantum computing 🧵
This was a challenging and exciting collaboration between @IBMResearch and @Mila_Quebec. Thank you @rndm_wlks, @flashlemonade, @anchowdhury13 and @k_neklyudov for helping to assemble such disconnected parts into a coherent whole!
This new bridge between disparate fields also serves as a kind of Rosetta stone, letting us cast ML questions as QC questions, and vice versa E.g., certain quantum states are hard to prepare on complexity-theoretic grounds, which may imply new limits on (classical!) flow models
Flow and diffusion models are the Schrödinger equation in disguise. That’s what we show in our recent paper: "Wavefunction Flows: Efficient Quantum Simulation of Continuous Flow Models" arxiv.org/abs/2510.08462 This has important consequences in both ML and quantum computing 🧵
Andreas Wallraff @AndreasAtETH
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Zlatko Minev @zlatko_minev
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彡 Nᗩᖇᒪi 彡 @BGnarli
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Sathwik-70B @VishnuSathvik1
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Thinker @Thinker_ML
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Anand C. Patel, MD MS @anandcpatelmdms
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David Harwood @dha019589
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visionawry @awryvision
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RUKHSAN UL HAQ @AnnalQuantumHaq
75 Followers 524 Following I am a quantum physicist working on quantum computation, quantum machine learning and deep learning.
Gilad @giladturok
2K Followers 6K Following Machine learning PhD student @cornell | diffusion language models | Prev: @Uber, @FlatironInst, @Columbia
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Earl T Campbell @earltcampbell
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Giuseppe Carleo @gppcarleo
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Joe Fitzsimons @jfitzsimons
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Aephraim Steinberg @QuantumAephraim
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Juan Felipe Carrasqui... @carrasqu
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Yinuo Ren @Yinuo_Ren
502 Followers 180 Following Kempner Research Fellow, @KempnerInst, @Harvard. PhD in Applied Mathematics @Stanford. Previously @BytedanceTalk Seed, @FlatironInst, @AmazonScience, @PKU1898.
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55K Followers 4 Following Automating discovery to accelerate science and engineering for the world.
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90K Followers 586 Following Old School Boston does not own or claim rights to any images. Photo submission via [email protected]
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Alexia Jolicoeur-Mart... @jm_alexia
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215 Followers 2K Following PhD student @UofTCompSci | @PNNLab | AI | Quantum Algorithms | Theorist | "It is a lot better to walk alone than with a crowd going in the wrong direction."
Majdi Hassan @majdi_has
289 Followers 258 Following PhD student @ Mila | ML for chemistry and biophysics
Anirban Chowdhury @anchowdhury13
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Peter Potaptchik @PPotaptchik
391 Followers 468 Following DPhil student at Oxford https://t.co/JH0l4u7wHv
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144K Followers 68 Following "My wish is for an America that matches the marketing material"
ICML Conference @icmlconf
89K Followers 11 Following Int'l Conf on Machine Learning • This account not monitored, Contact: https://t.co/6saHKWVxR6 • LinkedIn: https://t.co/YlU0lrSVna
Ross Douthat @Douthat60
228K Followers 455 Following 60 Minutes correspondent, Free Press columnist, author of Believe: https://t.co/knRQn31ehz and The Falcon's Children: https://t.co/NgELacKn0n
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Adam Brown @A_G_I_Joe
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Dominion Aesthetics @CanadianAesth
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Thomas G. Dietterich @tdietterich
65K Followers 660 Following University Distinguished Professor (Emeritus), Oregon State Univ.; Former President, AAAI; ArXiv Chair CS Section, Chair Editorial Advisory Council
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Differential Eqns @diff_eq
76K Followers 17 Following Tweets on ordinary and partial differential equations from @JohnDCook
Yilun Du @du_yilun
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Murray Campbell @murraycampbell
724 Followers 355 Following AI researcher. Co-creator of Deep Blue chess computer.
Dwarkesh Patel @dwarkesh_sp
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Scott Alexander @slatestarcodex
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Arnaud Doucet @ArnaudDoucet1
7K Followers 895 Following Senior Staff Research Scientist @GoogleDeepMind. Previously @UniofOxford.
Kyunghyun Cho @kchonyc
90K Followers 2K Following a mediocre combination of a mediocre professor at @nyuniversity and a mediocre CEO at @OrtetAI
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22K Followers 3K Following 🧙 RL @Reflection_AI past: @MetaAi @GoogleDeepmind @SCSatCMU @Cornell_Tech
Nando de Freitas @NandoDF
112K Followers 926 Following I seek to understand intelligence & agency and build AI aligned with compassion, freedom & universal human empowerment through progress in science & engineering
Lawrence H. Summers @LHSummers
367K Followers 712 Following Charles W. Eliot University Professor and President Emeritus at Harvard. Secretary of the Treasury for President Clinton and Director of NEC for President Obama
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84K Followers 370 Following Chief Research Officer at @OpenAI. Coach for the USA IOI Team.
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