@jamesallingham.bsky.social
Research Scientist @GoogleDeepMind | Organiser @DeepIndaba | Machine Learning PhD @CambridgeMLG | 🇿🇦
@fionalippert.bsky.social
Postdoc at SRON | PhD at AMLab & AI4Science Lab, University of Amsterdam Interested in AI for Earth science & ecology, hybrid modeling, geospatial machine learning
@adamgol.bsky.social
Apple ML Research in Barcelona, prev OxCSML InfAtEd, part of MLinPL & polonium_org 🇵🇱, sometimes funny
@lawrennd.bsky.social
Professor of Machine Learning, University of Cambridge, academic lead of ai@cam, Accelerate Science, author of The Atomic Human, proceedings editor for PMLR.
@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.
@combayns-workshop.bsky.social
Combining Bayesian and Neural approaches for Structured Data. ComBayNS workshop @ IJCNN 2025 Conference, Rome, June 30-July 2 2025.
@jeffdean.bsky.social
Google Chief Scientist, Gemini Lead. Opinions stated here are my own, not those of Google. Gemini, TensorFlow, MapReduce, Bigtable, Spanner, ML things, ...
@lacerbi.bsky.social
Assoc. Prof. of Machine & Human Intelligence | Univ. Helsinki & Finnish Centre for AI (FCAI) | Bayesian ML & probabilistic modeling | https://lacerbi.github.io/
@charlesm993.bsky.social
Research fellow at the Flatiron Institute and Stan developer. Research in statistics, ML, and AI for science. Views are my own. https://charlesm93.github.io./
@willieneis.bsky.social
Assistant Professor in CS + AI at USC. Previously at Stanford, CMU. Machine Learning, Decision Making, AI-for-Science, Generative AI, ML Systems, LLMs. https://willieneis.github.io
@arnauddoucet.bsky.social
Senior Staff Research Scientist @Google DeepMind, previously Stats Prof @Oxford Uni - interested in Computational Statistics, Generative Modeling, Monte Carlo methods, Optimal Transport.
@stephanmandt.bsky.social
AI Professor @UCIrvine | Formerly @blei_lab, @Princeton | #GenAI, #Compression, #AI4Science | General Chair @aistats_conf 2025 | AI Resident @ChanZuckerberg
@jwvdm.bsky.social
Associate Professor (UHD) at the University of Amsterdam. Probabilistic methods, deep learning, and their applications in science in engineering.
@monaschir.bsky.social
PhD candidate @amlab.bsky.social @ellis.eu Probabilistic Machine Learning | Sequence Models
@louissharrock.bsky.social
Postdoc in Statistical Machine Learning @ Lancaster Uni. Previously PhD @ Imperial College London, MA @ Cambridge Uni. Interested in computational statistics, probabilistic machine learning, optimisation. Website: https://louissharrock.github.io/
@arxiv-stat-ml.bsky.social
source: https://arxiv.org/rss/stat.ML maintainer: @tmaehara.bsky.social
@arxiv-cs-cc.bsky.social
Computer Science -- Computational Complexity (cs.CC) source: https://export.arxiv.org/rss/cs.CC maintainer: @tmaehara.bsky.social
@arxiv-cs-ds.bsky.social
Computer Science -- Data Structures and Algorithms (cs.DS) source: https://export.arxiv.org/rss/cs.DS maintainer: @tmaehara.bsky.social
@spmontecarlo.bsky.social
Lecturer in Maths & Stats at Bristol. Interested in probabilistic + numerical computation, statistical modelling + inference. (he / him). Homepage: https://sites.google.com/view/sp-monte-carlo Seminar: https://sites.google.com/view/monte-carlo-semina
@davidpfau.com
So far I have not found the science, but the numbers keep on circling me. Views my own, unfortunately.
@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.
@ccanonne.github.io
Senior Lecturer #USydCompSci at the University of Sydney. Postdocs IBM Research and Stanford; PhD at Columbia. Converts ☕ into puns: sometimes theorems. He/him.
@zacharylipton.bsky.social
Cofounder & CTO @ Abridge, Raj Reddy Associate Prof of ML @ CMU, occasional writer, relapsing 🎷, creator of d2l.ai & approximatelycorrect.com
@alexlew.bsky.social
Theory & practice of probabilistic programming. Current: MIT Probabilistic Computing Project; Fall '25: Incoming Asst. Prof. at Yale CS
@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/
@karen-ullrich.bsky.social
Research scientist at FAIR NY ❤️ Machine Learning + Information Theory. Previously, PhD at UoAmsterdam, intern at DeepMind + MSRC.
@randomlywalking.bsky.social
Research Scientist, Google DeepMind / Ex-academic / Deep learning to help people write code / ❤️s:🐱🐶☕️🍕
@yaringal.bsky.social
Associate Professor of Machine Learning, University of Oxford; OATML Group Leader; Director of Research at the UK government's AI Safety Institute (formerly UK Taskforce on Frontier AI)
@tkipf.bsky.social
Research at Google DeepMind. Ex-Physicist. Controllable World Simulators (GNNs, Structured World Models, Neural Assets). 📍 San Francisco, CA
@stephanhoyer.com
Building AI climate models at Google. I also contribute to the scientific Python ecosystem, including Xarray, NumPy and JAX. Opinions are my own, not my employer's.
@avehtari.bsky.social
Professor in computational Bayesian modeling at Aalto University, Finland. Bayesian Data Analysis 3rd ed, Regression and Other Stories, and Active Statistics co-author. #mcmc_stan and #arviz developer. Also in Mastodon: https://bayes.club/@avehtari
@patrickkidger.bsky.social
I do SciML + open source! 🧪 ML+proteins @ http://Cradle.bio 📚 Neural ODEs: http://arxiv.org/abs/2202.02435 🤖 JAX ecosystem: http://github.com/patrick-kidger 🧑💻 Prev. Google, Oxford 📍 Zürich, Switzerland
@iclr-conf.bsky.social
International Conference on Learning Representations https://iclr.cc/
@phillip-lippe.bsky.social
Research Scientist GoogleDeepMind. Working on large-scale pretraining at Gemini. https://phlippe.github.io/
@philipphennig.bsky.social
Professor for AI/ML Methods in Tübingen. Posts about Probabilistic Numerics, Bayesian ML, AI for Science. Computations are data, Algorithms make assumptions.
@jmtomczak.bsky.social
Group Leader, Generative AI | NeurIPS 2024 Program Chair | Principal Scientist & Director | Founder of Amsterdam AI Solutions
@lucamb.bsky.social
Assistant professor in Machine Learning and Theoretical Neuroscience. Generative modeling and memory. Opinionated, often wrong.
@olgatticus.bsky.social
MSCA PhD student at AMLab with Erik Bekkers, interested in geometric deep learning, generative models and their intersection 🌐 ✨ bit.ly/olga-zaghen