@davidpfau.com
So far I have not found the science, but the numbers keep on circling me. Views my own, unfortunately.
@finbarr.bsky.social
building the future research at midjourney, deepmind. slinging ai hot takes 🥞at artfintel.com
@timpmorris.bsky.social
Principal research fellow in statistical methods. Work on simulation studies, non-inferiority, missing data, estimands, covariate adjustment… He/him https://tpmorris.substack.com/ https://profiles.ucl.ac.uk/2059
@approxbayesseminar.bsky.social
Posting about the One World Approximate Bayesian Inference (ABI) Seminar, details at https://warwick.ac.uk/fac/sci/statistics/news/upcoming-seminars/abcworldseminar/
@maartenvsmeden.bsky.social
statistician • associate prof • team lead health data science and head methods research program at julius center • director ai methods lab, umc utrecht, netherlands • views and opinions my own
@gsimpson.bsky.social
(Palaeo)[ecologist | limnologist] & #fakeStatistican, #rstats user, wielder of #GAMs. He/him/his. Opinions mine…
@jonthegeek.com
🗣️#RStats #DataScience #Dogs @dslc.io Executive Director #TidyTuesday poster 🔗http://linkedin.com/in/jonthegeek 🔗http://github.com/jonthegeek
@mgorinova.bsky.social
ex-@TwitterCortex @Birdwatch 💙 | Now LLMs for innovation & IP 🚀 | PhD in probabilistic machine learning, loyal servant to a cat, collector of random variables, lover of well-placed puns https://mgorinova.github.io/
@alexlew.bsky.social
Theory & practice of probabilistic programming. Current: MIT Probabilistic Computing Project; Fall '25: Incoming Asst. Prof. at Yale CS
@jwvdm.bsky.social
Associate Professor (UHD) at the University of Amsterdam. Probabilistic methods, deep learning, and their applications in science in engineering.
@lambdaphdp.bsky.social
Exploring {Probabilistic Programming w/ Typed λ-Calculi; Lean; Program Synthesis; Self-Improving A.I.; Evolutionary Genetics} @ umontreal. Ph.D. USherbrooke
@spinkney.bsky.social
I mostly post about probabilistic programming stuff, statistics, and R/Julia/Python (in that order). I'm a volunteer Stan developer and citizen scientist (papers on arxiv). Currently my day job is doing marketing analytics.
@trappmartin.bsky.social
ML Researcher @ Aalto University 🇫🇮. Doing: Probabilistic ML | probabilistic circuits | (Bayesian) deep learning | Bayesian stats https://trappmartin.github.io/
@osazuwa.bsky.social
Probabilistic machine Learning, causal inference, language models. Teach at http://Altdeep.ai & @Northeastern, work at @MSFTResearch.
@aloctavodia.bsky.social
Research Fellow at Aalto University. Open source contributor #ArviZ, #Bambi, #Kulprit, #PreliZ, #PyMC, #PyMC-BART. Support me at https://ko-fi.com/aloctavodia https://bayes.club/@aloctavodia
@pymc-labs.bsky.social
The Bayesian Consultancy • Using PyMC to solve your most challenging data science problems • http://pymc-labs.com
@mschauer.bsky.social
Statistician, Associate Professor (Lektor) at University of Gothenburg and Chalmers; inference and conditional distributions for anything https://mschauer.github.io http://orcid.org/0000-0003-3310-7915 [ˈmoː/r/ɪts ˈʃaʊ̯ɐ]
@cfreer.bsky.social
Research Scientist at MIT studying interactions of randomness and computation
@cameron.pfiffer.org
AI systems, financial economics PhD, ATProto fan, man with tattooed legs Signal: https://signal.me/#eu/AQ1ajwHwgg0rabcRsdtkm9UYpdg52axiruSTFMmrFy0LR4Ds8pdH25jzjoTc2bGu
@colcarroll.bsky.social
Runner, biker, hiker. Software engineer @DeepMind, and open source enthusiast. Sometimes crafts things out of wood. he/his.
@guyvdb.bsky.social
🎓 CS Prof at UCLA 🧠 Researching reasoning and learning in artificial intelligence: tactable deep generative models, probabilistic circuits, probabilistic programming, neurosymbolic AI https://web.cs.ucla.edu/~guyvdb/
@xuanalogue.bsky.social
PhD Student. MIT ProbComp / CoCoSci. Inverting Bayesian models of human reasoning and decision-making. Pronouns: 祂/伊
@arviz.bsky.social
Official account for the ArviZ project. We provide #FOSS tools for exploratory analysis of #Bayesian models in #Python and #JuliaLang www.arviz.org
@sethaxen.com
Empowering scientists with machine learning @mlcolab.org. Sometimes #Bayesian. Usually #FOSS. Preferably in #JuliaLang. Expat: 🇺🇸 ➡️ 🇩🇪 💼 On the job market (remote/Stuttgart area) sethaxen.com
@poorvagarg.bsky.social
Working on Probabilistic Programming Languages https://web.cs.ucla.edu/~poorvagarg/
@sholtzen.bsky.social
I like computers. assistant prof at northeastern https://www.khoury.northeastern.edu/home/sholtzen/
@thomas-pinder.bsky.social
Bayesian statistics, Gaussian processes, and all things ML. Senior Applied Scientist at Amazon and developer of GPJax.
@nolovedeeplearning.bsky.social
human being | assoc prof in #ML #AI #Edinburgh | PI of #APRIL | #reliable #probabilistic #models #tractable #generative #neuro #symbolic | heretical empiricist | he/him 👉 https://april-tools.github.io
@vincefort.bsky.social
PI at Helmholtz AI, Faculty at TU Munich, Fellow at Zuse School for reliable AI, Branco Weiss Fellow, ELLIS Scholar. Prev: Cambridge CBL, St John's College, ETH Zürich, Google Brain, Microsoft Research, Disney Research. https://fortuin.github.io/
@sbi-devs.bsky.social
Community-maintained simulation-based inference (SBI) toolkit in PyTorch: • NPE, NLE & NRE • amortized and sequential inference • wide range of diagnostics Posts written by @deismic.bsky.social & @janboelts.bsky.social. 🔗 https://github.com/sbi-dev/sbi
@treichelt.bsky.social
postdoc @ uni oxford. machine learning. climate. statistics. web: treigerm.github.io
@ellieyhc.bsky.social
PhD student @mit_csail | Programming Systems for AI/ML | don’t ask how many cups of coffee I’ve drank
@mlbowers.bsky.social
PhD student at MIT studying program synthesis, probabilistic programming, and cognitive science. she/her
@kartikchandra.bsky.social
I'm a PhD student at MIT CSAIL. More about me: https://cs.stanford.edu/~kach
@roydanroy.bsky.social
Research Director, Founding Faculty, Canada CIFAR AI Chair @VectorInst. Full Prof @UofT - Statistics and Computer Sci. (x-appt) danroy.org I study assumption-free prediction and decision making under uncertainty, with inference emerging from optimality.
@ravenwater.bsky.social
Accelerating innovation, solving problems through high-performance compute, computational engineering entrepreneur, inventor of Domain Flow
@lacerbi.bsky.social
Assoc. Prof. of Machine & Human Intelligence | Univ. Helsinki & Finnish Centre for AI (FCAI) | Bayesian ML & probabilistic modeling | https://lacerbi.github.io/
@jjcmoon.bsky.social
PhD student @ KU Leuven | maene.dev | #neurosymbolic learning & #probabilistic reasoning