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            Application for a postdoc research fellowship in computational mathematics at the Flatiron Institute in New York are now open!
apply.interfolio.com/173401
๐ Deadline is December 1st.
๐ญ This is an excellent place to do research at the interface of ML, stats and the natural sciences.
               
            
            
                16.09.2025 23:55 โ ๐ 1    ๐ 1    ๐ฌ 1    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
    
    
            I also like to describe this paper as a discussion on what is the best circle to approximate an ellipse :)
๐งต 4/4
               
            
            
                10.09.2025 00:33 โ ๐ 0    ๐ 0    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
    
    
            This paper contributes to the foundational theory of VI, and dives deep into both conceptual and practical questions such as: How do we measure uncertainty in high-dimensions? How should we measure discrepancy between probability distributions?
๐งต 3/
               
            
            
                10.09.2025 00:33 โ ๐ 0    ๐ 0    ๐ฌ 1    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
    
    
            The two main results of the paper are:
1๏ธโฃ An impossibility theorem that shows that any factorized (mean-field) approximation of VI can at beast learn one of three measures of uncertainty
2๏ธโฃ An ordering of divergences used as objectives for VI based on the uncertainty in their approximation. 
๐งต 2/
               
            
            
                10.09.2025 00:33 โ ๐ 0    ๐ 0    ๐ฌ 1    ๐ 0                      
            
         
            
        
            
            
            
            
                                                
                                                
    
    
    
    
            My paper with Loucas Pillaud-Vivien and Lawrence Saul, โVariational Inference for Uncertainty Quantification: An Analysis of Trade-offsโ, has been accepted for publication in the Journal of Machine Learning Research.
๐ arxiv.org/abs/2403.13748
๐งต 1/
               
            
            
                10.09.2025 00:28 โ ๐ 16    ๐ 5    ๐ฌ 1    ๐ 0                      
            
         
            
        
            
        
            
            
            
            
            
    
    
            
                        
                Charles Margossian Joins the UBC Department of Statistics | UBC Statistics
                
            
        
    
    
            Yes, in principle, I start at UBC Statistics today. But right now, I'm running around the Frankfurt airport to catch my flight to Vancouver .... ๐โโ๏ธ๐งณโ๏ธ
www.stat.ubc.ca/news/charles...
               
            
            
                01.08.2025 10:29 โ ๐ 3    ๐ 0    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
        
            
            
            
            
            
    
    
    
    
            ๐ My course: "Bayesian Statistics: a practical introduction." We covered Bayesian models (priors and likelihoods), Markov chain Monte Carlo and uncertainty aware cross-validation. Most of our discussion was motivated by an example from epidemiology.
               
            
            
                28.07.2025 15:31 โ ๐ 2    ๐ 0    ๐ฌ 1    ๐ 0                      
            
         
            
        
            
        
            
            
            
            
            
    
    
    
    
            ๐จโ๐ป Credit also to Brian Ward and Steve Bronder for their contribution to the C++ implementation and integration with the Stan ecosytem. (From what I understand, WALNUTS is not part of the next Stan release but you can use it on models written in Stan!!)
               
            
            
                26.06.2025 06:03 โ ๐ 0    ๐ 0    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
            
            
            
                                                
                                                
    
    
    
    
            New manuscript by Nawaf Bou-Rabee, Bob Carpenter, Tore Kleppe and Sifan Liu on the WALNUTS algorithm which improves of the NUTS sampler by introducing a locally adaptive step size.
๐  Paper: arxiv.org/pdf/2506.18746
๐ป Code: github.com/bob-carpente...
               
            
            
                26.06.2025 06:00 โ ๐ 13    ๐ 6    ๐ฌ 2    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
    
    
            ๐ธ๐ฌ Next stop: Singapore for BayesComp'25 (bayescomp2025.sg) The organizers put together a wonderful program!
I'll be:
๐ช chairing the session on "Parallel comp for MCMC"
๐๏ธ speaking at the session on "Advances in VI"
Looking forward to meeting researchers and catching up with colleagues.
               
            
            
                15.06.2025 11:23 โ ๐ 8    ๐ 2    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
            
            
            
                                                
                                                
    
    
    
    
            Research opportunity for a graduate student in ecology ๐ณ at UBC ๐จ๐ฆ with Lizzie Wolkovich and the Temporal Ecology lab (temporalecology.org).
๐ Apply here: temporalecology.org/joining-the-... by July 1st 2025!
The abstract sounds fascinating (see attached).
               
            
            
                13.06.2025 21:28 โ ๐ 0    ๐ 2    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
            
                            
                        
                CmdStan & Stan 2.37 release candidate
                I am happy to announce that the latest release candidates of CmdStan and Stan are now available on Github!  This release cycle brings the embedded Laplace approximation, a sum-to-zero matrix type, new...
            
        
    
    
            ๐งโ๐ป Candidate release for Stan 2.37 is out: discourse.mc-stan.org/t/cmdstan-st.... Lots of exciting features to try out, including:
- embedded/integrated Laplace approximation
- new constrained types (e.g. sum_to_zero_matrix)
- built-in constraint transformations exposed
               
            
            
                09.06.2025 18:08 โ ๐ 3    ๐ 1    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
        
            
            
            
            
                                                
                                                
    
    
    
    
            ๐This award is this much more meaningful to me in that it celebrates my collaboration with the amazing Lawrence Saul (users.flatironinstitute.org/~lsaul/).
               
            
            
                05.05.2025 01:18 โ ๐ 0    ๐ 0    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
    
    
            ๐กWe provide theory on VI's ability to recover certain statistics, despite misspecification---that is in settings where we  do NOT drive the KL-divergence to 0.
๐ VI is provably good at recovering the mean and correlation matrix.
               
            
            
                05.05.2025 01:17 โ ๐ 0    ๐ 0    ๐ฌ 1    ๐ 0                      
            
         
            
        
            
        
            
            
            
            
                                                
                                                
    
    
    
    
            ๐น๐ญ Just arrived in Phuket, Thailand for #AISTATS 2025.
๐ I'll presenting my recent work with Lawrence Saul on Variational Inference in Location-Sacale Families: arxiv.org/abs/2410.11067
DM if you are in town and want to connect at the conference!
               
            
            
                01.05.2025 18:00 โ ๐ 6    ๐ 1    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
            
            
            
                                                
                                                
    
    
    
    
            For the first time, Journal-to-Conference papers have entered the schedule of #AISTATS2025 ๐ 
To celebrate here is a bingo card: should you be among the first to meet all of our amazing Journal-to-Conference presenters (I need proof!), Iโll buy you a drink... provided that you can find me too!
               
            
            
                28.04.2025 04:29 โ ๐ 13    ๐ 2    ๐ฌ 2    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
    
    
            ๐ Putting together a reading list for #AISTATS 2025. I already found a few very good papers, and I'm curious to hear about more accepted publications.
               
            
            
                21.04.2025 14:13 โ ๐ 1    ๐ 0    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
            
                            
                        
                Elections for Stan Governing Body 2025
                Itโs this time of the year again! (And in fact, weโre a little bit overdue.)  Weโre renewing the Stan Governing Body (SGB) with all 5 seats up for grabs. Current SGB members may still run, however the...
            
        
    
    
            ๐ฃ Nominations for the Stan Governing Body are open for another two weeks. Calling on all members of the Stan community to consider this role.
๐ discourse.mc-stan.org/t/elections-...
๐ก A post about my own experience: statmodeling.stat.columbia.edu/2025/03/15/e...
               
            
            
                16.04.2025 16:03 โ ๐ 0    ๐ 2    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
    
    
            I'm thrilled to share that, starting this summer, I will continue my academic journey as an assistant professor of statistics at the University of British Columbia in Vancouver, Canada.
Full statement here: charlesm93.github.io/files/letter...
               
            
            
                20.03.2025 18:56 โ ๐ 25    ๐ 1    ๐ฌ 5    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
            
                            
                        
                Petition to form a Bayesian Deep Learning section at ISBA
                Petition to form a Bayesian Deep Learning section at ISBA   We, the undersigned members of the International Society for Bayesian Analysis (ISBA), petition the ISBA board to establish a new Bayesian D...
            
        
    
    
            ๐ Exciting news! We're proposing a new *Bayesian Deep Learning* section within @isba-bayesian.bsky.social .
If you support this initiative, add your name to the petition and help make it happen! 
๐ Petition: tinyurl.com/527vaamz
Sinead Williamson, Theo Papamarkou @vincefort.bsky.social Sara Wade
1/2
               
            
            
                17.03.2025 22:35 โ ๐ 10    ๐ 4    ๐ฌ 1    ๐ 3                      
            
         
            
        
            
            
            
            
            
    
    
            
                        
                
Elections for the Stan Governing Body 2025 | Statistical Modeling, Causal Inference, and Social Science	
                
            
        
    
    
            A longer post on the election and my own experience on the SGB: statmodeling.stat.columbia.edu/2025/03/15/e...
... as well as some thoughts trying to both be a good developer and a good PhD student.
               
            
            
                15.03.2025 23:09 โ ๐ 1    ๐ 1    ๐ฌ 0    ๐ 0                      
            
         
            
        
            
        
            
            
            
            
            
    
    
    
    
            ๐ฃ Calling all members of the Stan community to action! 
โWe're renewing the Stan Governing Body. This is a fantastic way to contribute to the project. The SGB co-organizes StanCon and related events, funds developers, and helps set the directions of the project.
๐งต Link in thread.
               
            
            
                14.03.2025 19:05 โ ๐ 3    ๐ 3    ๐ฌ 1    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
            
                            
                        
                StanBio Connect 2025 โ StanBio Connect
                Advancing Biomedical Research with Stan
            
        
    
    
            StanConnects are a series of one-day online conferences for the application of Stan to specific areas. This year, we're kicking off with Stan for biology (broadly defined), co-organized by @ericnovik.bsky.social and @vianeylb.bsky.social, on 30 May '25!!
stanbio.org
               
            
            
                13.03.2025 15:39 โ ๐ 9    ๐ 4    ๐ฌ 1    ๐ 0                      
            
         
            
        
            
            
            
            
            
    
    
    
    
            With all that said: no, I do not use the same tools as 3blue1brown. My animations are super basic (done in keynote). But we have similar color palettes.
               
            
            
                13.02.2025 21:35 โ ๐ 1    ๐ 0    ๐ฌ 0    ๐ 0                      
            
         
    
         
        
            
        
                            
                    
                    
                                            Expressive probabilistic programming language for writing statistical models. Fast Bayesian inference. Interfaces for Python, Julia, R, and the Unix shell. A rich ecosystem of tools for validation and visualization. 
Home https://mc-stan.org/
                                     
                            
                    
                    
                                            Association for Uncertainty in AI. 
Upcoming conference: #uai2025 July 21-25th in Rio de Janeiro, Brazil ๐ง๐ท !
https://auai.org/uai2025
                                     
                            
                    
                    
                                            Team leader (tenured) at RIKEN AIP. Opinions my own. https://emtiyaz.github.io
๐ bridged from https://mastodon.social/@emtiyaz on the fediverse by https://fed.brid.gy/
                                     
                            
                    
                    
                                            Organisme public ๐ซ๐ท de recherche pluridisciplinaire, le Centre national de la recherche scientifique c'est 33 000 personnes qui font avancer la connaissance. #HelloESR
                                     
                            
                    
                    
                                            dad from hampshire, mostly found on linkedin talking stats
                                     
                            
                    
                    
                                            (astro)Physics PhD candidate @ Stony Brook. Astrobites alum. From Kazakhstan ๐ฐ๐ฟ. She/her.
Musical theater nerd, so pretty much insufferable. 
Statistics, planets, and stellar cartography.
https://ssagynbayeva.github.io
                                     
                            
                    
                    
                                            Statistician,Mother,Prof,Grandmother(she/her)๐ซ๐ท๐ต๐น๐บ๐ธ๐งช.
๐๏ธwith @wkhuber.bsky.social:Modern Statistics for Modern Biology (https://www.huber.embl.de/msmb/) #stats,#rstats.OSS,arXiv, microbial ecology,cytof,multi-omics,Bioconductor:phyloseq, DADA2
                                     
                            
                    
                    
                                            Amortized Bayesian Workflows in Python.
๐ฒ Post author sampled from a multinomial distribution, choices 
โ
 @marvin-schmitt.com
โ
 @paulbuerkner.com
โ
 @stefanradev.bsky.social
๐ GitHub github.com/bayesflow-org/bayesflow
๐ฌ Forum discuss.bayesflow.org
                                     
                            
                    
                    
                                            R, data, ๐, ๐ธ, ๐. He/him.
                                     
                            
                    
                    
                                            Full Professor of Computational Statistics at TU Dortmund University
Scientist | Statistician | Bayesian | Author of brms | Member of the Stan and BayesFlow development teams
Website: https://paulbuerkner.com
Opinions are my own
                                     
                            
                    
                    
                                            PhD student at UCL Statistical Science working at the intersection of Bayesian modelling and computation
                                     
                            
                    
                    
                                            Postdoc in machine learning at the Technical University of Denmark (DTU) ๐ฉ๐ฐ. PhD from DTU ๐ฉ๐ฐ. Spent time at Cambridge CBL ๐ฌ๐ง, UBC ๐จ๐ฆ, and University of Padova ๐ฎ๐น.
https://federicobergamin.github.io/
                                     
                            
                    
                    
                                            Graduate Student - Interested in RL and its mathematics ๐พ
> https://amirhosein-mesbah.github.io/
                                     
                            
                    
                    
                                            Studying neural computation โข Assistant Professor of Neuroscience at Baylor College of Medicine โข lipshutzlab.com
                                     
                            
                    
                    
                                            Bayesian and Julia software developer @ PlantingSpace
                                     
                            
                    
                    
                                            Postdoc at the University of Milan, member of the LAILA Lab
https://emmanuelesposito.it
                                     
                            
                    
                    
                                            Deep Learning x {Symmetries, Structures, Randomness} ๐ฆ 
Researcher at Flatiron Computational Maths in NYC. PhD from EPFL. https://www.bsimsek.com/
                                     
                            
                    
                    
                                            Probabilistic Machine Learning for Molecular Discovery
                                     
                            
                    
                    
                                            Assistant Prof @ImperialCollege. Applied Bayesian inference, spatial stats and deep generative models for epidemiology. Passionate about probabilistic programmingโcheck out my evolving #Numpyro course: https://elizavetasemenova.github.io/prob-epi ๐
                                     
                            
                    
                    
                                            Interests on bsky: ML research, applied math, and general mathematical and engineering miscellany. Also: Uncertainty, symmetry in ML, reliable deployment; applications in LLMs, computational chemistry/physics, and healthcare. 
https://shubhendu-trivedi.org