An interlude about structure computation, SSM and attention. Myosotis: arxiv.org/abs/2509.20503
26.09.2025 08:56 β π 1 π 1 π¬ 1 π 0
Exciting news: AMLab is happy to have 7 papers accepted at #ICML2025! π
See the thread below for the full list π and meet us in Vancouver to discuss them further! π¨π¦
π§΅1 / 8
06.05.2025 14:53 β π 14 π 4 π¬ 1 π 0
NeurIPS Poster VISA: Variational Inference with Sequential Sample-Average ApproximationsNeurIPS 2024
I'm gonna be at #Neurips this week to present our work on variational inference with sequential sample-average approximations (neurips.cc/virtual/2024...). I'm also on the job market!
Happy to chat all things probabilistic modeling and inference!
10.12.2024 18:10 β π 3 π 0 π¬ 0 π 0
πͺͺVISA: Variational Inference with Sequential Sample-Average Approximations
by @zmheiko.bsky.social, @canaesseth.bsky.social, @jwvdm.bsky.social
πͺͺhttps://neurips.cc/virtual/2024/poster/93819
πhttps://arxiv.org/abs/2403.09429
π§΅8 / 12
09.12.2024 13:24 β π 6 π 3 π¬ 1 π 1
If you are attending #NeurIPS2024π¨π¦, make sure to check out AMLab's 11 accepted papers ...and to have a chat with our members there! π©βπ¬π»β
Submissions include generative modelling, AI4Science, geometric deep learning, reinforcement learning and early exiting. See the thread for the full list!
π§΅1 / 12
09.12.2024 13:24 β π 25 π 7 π¬ 1 π 0
Research Scientist @GoogleDeepMind | Organiser @DeepIndaba | Machine Learning PhD @CambridgeMLG | πΏπ¦
Postdoc at SRON | Previously PhD at AMLab & AI4Science Lab, University of Amsterdam
Interested in AI for Earth science & ecology, hybrid modeling, geospatial machine learning
Apple ο£Ώ ML Research in Barcelona, prev OxCSML InfAtEd, part of MLinPL & polonium_org π΅π±, sometimes funny
Professor of Machine Learning, University of Cambridge, academic lead of ai@cam, Accelerate Science, author of The Atomic Human, proceedings editor for PMLR.
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.
Combining Bayesian and Neural approaches for Structured Data.
ComBayNS workshop @ IJCNN 2025 Conference, Rome, June 30-July 2 2025.
MailMate is an email client for macOS only.
Google Chief Scientist, Gemini Lead. Opinions stated here are my own, not those of Google. Gemini, TensorFlow, MapReduce, Bigtable, Spanner, ML things, ...
PhD student in the Machine Learning Group, Cambridge.
Assoc. Prof. of Machine & Human Intelligence | Univ. Helsinki & Finnish Centre for AI (FCAI) | Bayesian ML & probabilistic modeling | https://lacerbi.github.io/
Prof at the University of British Columbia. Research in statistics, ML, and AI for science. Views are my own. https://charlesm93.github.io./
π§π»ββοΈ scientist at Meta NYC | http://bamos.github.io
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
Senior Staff Research Scientist @Google DeepMind, previously Stats Prof @Oxford Uni - interested in Computational Statistics, Generative Modeling, Monte Carlo methods, Optimal Transport.
Abolish the value function!
AI Professor @UCIrvine | Formerly @blei_lab, @Princeton | #GenAI, #Compression, #AI4Science | General Chair @aistats_conf 2025 | AI Resident @ChanZuckerberg
Associate Professor (UHD) at the University of Amsterdam. Probabilistic methods, deep learning, and their applications in science in engineering.
PhD candidate @amlab.bsky.social @ellis.eu
Probabilistic Machine Learning | Sequence Models
Lecturer (Assistant Prof) in Statistical Science at UCL.
Previously Postdoc @ Lancaster Uni, PhD @ Imperial College London, MA @ Cambridge Uni.
Interested in computational stats, probabilistic ML, optimisation.
Website: https://louissharrock.github.io/
