Just published in JOSS: 'Bamojax: Bayesian Modelling with JAX' https://doi.org/10.21105/joss.08642
27.10.2025 17:12 β π 1 π 1 π¬ 0 π 0@maxhinne.bsky.social
Associate professor, Bayesian stats, ML, at the Donders Institute for Brain, Cognition, and Behaviour, Radboud University. Might also follow foodies and sci-fi writers.
Just published in JOSS: 'Bamojax: Bayesian Modelling with JAX' https://doi.org/10.21105/joss.08642
27.10.2025 17:12 β π 1 π 1 π¬ 0 π 0It's actually been super useful for us in several GP related models!
16.10.2025 07:06 β π 0 π 0 π¬ 0 π 0Bamojax (Bayesian modelling with JAX) v0.3.10 is out! Next to increased support for distributions and bijectors, several marginal likelihood estimators are now available, such as bridge sampling and truncated harmonic mean estimation (THAMES).
Check it out on github.com/UncertaintyI...!
Very proud on David Leeftink's first PhD thesis paper on optimal control of probabilistic dynamics models! Check it out here: arxiv.org/abs/2504.02543
03.09.2025 15:11 β π 3 π 0 π¬ 0 π 0After five years of confused staring at Greek letters, it is my absolute pleasure to finally share our (with @smfleming.bsky.social) computational model of mental imagery and reality monitoring: Perceptual Reality Monitoring as Higher-Order inference on Sensory Precision β¨
osf.io/preprints/ps...
Na een lange en chaotische avond, stemde de Tweede Kamer voor de asielwetten van minister Faber.
Het wordt zΓ©lfs strafbaar om ongedocumenteerde mensen te helpen met onderdak, een maaltijd of kleding.
Help ons dit beleid tegen te houden, teken Γ©n deel de petitie:
groenlinkspvda.nl/petitie/stop...
I am in downtown Los Angeles right now and it is completely surreal to hear that Trump is sending Marines here. We are listening to mariachi music. People have dogs. There are teenagers here. It is utterly and completely peaceful. Please tell your friends.
09.06.2025 21:28 β π 12519 π 5624 π¬ 209 π 247Job Alert! Two PhD positions in the Probabilistic Graphical Models group of the @DondersInst at @RadboudU. Both PhDs are part of the ELSA lab on Legal, Regulatory, and Policy Aspects of Clinical Decision Support Systems. 1/8
13.05.2025 16:11 β π 1 π 1 π¬ 1 π 0Bayes-by's first Markov chain? :o)
30.04.2025 14:24 β π 1 π 0 π¬ 1 π 0Picture of the abstract of our new paper
Picture of our key results (Figure 1)
π Effects of climate protests by scientists paper published!
Our findings suggest that scientists can engage in public protest without compromising their credibility, but that such actions alone may have less impact than one would like to believe: royalsocietypublishing.org/doi/10.1098/...
My lab is looking for a PhD candidate, in collaboration with βBernhard Englitzβ's lab.
www.ru.nl/en/working-a...
"...for every Β£1 of public money invested into UK universities, Β£14 of economic benefit is generated" www.universitiesuk.ac.uk/latest/news/...
12.04.2025 04:51 β π 3 π 1 π¬ 0 π 0Long COVID advocates and researchers in the United States have done the extraordinary. After a bruising battle, they managed to revive some of the research grants cancelled by the administration of President Donald Trump.
https://go.nature.com/3RKg5tP
David Leeftink's first PhD thesis work is now available on arXiv! Probabilistic Pontryagin's Maximum Principle for Continuous-Time Model-Based Reinforcement Learning, check it out!
05.04.2025 17:21 β π 2 π 2 π¬ 0 π 0Join us in Amsterdam for the 11th Model-Based Neuroscience & Cognition Summer School. Gain a solid foundation in Bayesian evidence-accumulation modeling and explore its integration with neuroscience or advanced computational frameworks, including reinforcement-learning models. modelbasedneurosci.com
28.03.2025 15:00 β π 14 π 12 π¬ 0 π 0My tutorial on Sequentual Monte Carlo for psychology and behavioural science is out now in Behavior Research Methods! Check it out at link.springer.com/article/10.3...
26.03.2025 15:42 β π 20 π 10 π¬ 0 π 07/ Much more interesting examples, ranging from variable selection to Wishart processes, can be found at https://github.com/UncertaintyInComplexSystems/bamojax/tree/main/bamojax/examples
Happy modelling!
6/ model = Model('Gaussian with unknown mean')
unknown_mean = model.add_node('mu', distribution=dx.Normal(loc=mu0, scale=sd0))
y = model.add_node('y', distribution=dx.Normal, observations=y, parents=dict(loc=unknown_mean, scale=true_sd))
5/ Here is a very simple model, where we estimate the mean of a Gaussian using bamojax. We use Distrax to define probability distributions:
24.03.2025 12:05 β π 0 π 0 π¬ 1 π 04/ In contrast to deriving a log-density from e.g. PyMC and using Blackjax to sample from it, with *bamojax* you have fine-grained control over individual Gibbs steps, which leads to much more efficient inference.
24.03.2025 12:05 β π 0 π 0 π¬ 1 π 03/ This makes it possible to have *both* fast modelling, and fast inference!
24.03.2025 12:05 β π 0 π 0 π¬ 1 π 02/ Very fast Bayesian inference in JAX is possible through Blackjax, but model development is easier in probabilistic programming languages like Stan and PyMC. *bamojax* provides automated Gibbs sampling, using the different sampling algorithms provided by Blackjax to update individual variables.
24.03.2025 12:05 β π 1 π 0 π¬ 1 π 0π§΅ Introducing *bamojax* v0.1 --- Bayesian Modelling in JAX! https://github.com/uncertaintyincomplexsystems/bamojax
24.03.2025 12:05 β π 0 π 0 π¬ 1 π 0Ufff this went from bad to downright horrifying in less than a week :'-(
02.02.2025 11:39 β π 1 π 0 π¬ 1 π 0