Moritz Schauer
@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]
https://mschauer.github.io
http://orcid.org/0000-0003-3310-7915
[ˈmoː/r/ɪts ˈʃaʊ̯ɐ]
God made not only the numbers but also a sequence of independent standard normal random variables.
November 12, 2025 at 2:31 AM
God made not only the numbers but also a sequence of independent standard normal random variables.
The (samizdat?) solution book to the classic soviet era “Problems In Mathematical Analysis” by Demidovich was called “Anti-Demidovich” by the students. 😀
November 10, 2025 at 12:10 PM
The (samizdat?) solution book to the classic soviet era “Problems In Mathematical Analysis” by Demidovich was called “Anti-Demidovich” by the students. 😀
The event B having happened is not the same as the receiving the information O that the event B has happened, because you also condition on receiving the information at all in the latter case. Conflating this contributes a lot to the "paradoxa" such as boy/girl paradox, Monty Hall...
![For the applicability of Bayes' theorem, it is important when the information $B$ you condition on is actually available.
Let $O \subset B$ be the event of observing $B$ with $P(O)>0$. If $O$ and $A$ are independent with respect to $P_{|B}(\cdot) = P(\cdot \mid B)$,
then
\[
P(A\mid O) = P(A \mid B).
\]](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:weizynbs42yzl4y6de3z4dvu/bafkreihnkdxbvmdk4um6how7qgvurwhfhrkqhlu4baqlnkeepd7z4kkjfe@jpeg)
November 6, 2025 at 11:09 AM
The event B having happened is not the same as the receiving the information O that the event B has happened, because you also condition on receiving the information at all in the latter case. Conflating this contributes a lot to the "paradoxa" such as boy/girl paradox, Monty Hall...
Reposted by Moritz Schauer
Excited to share our recent paper, ”Compressing Biology,” to be presented at the Imageomics workshop at NeurIPS 2025. 🔬💻 Work led by my amazing PhD student Télio Cropsal. #cellpainting #stablediffusion #imageomics
arxiv.org/abs/2510.19887
arxiv.org/abs/2510.19887
Compressing Biology: Evaluating the Stable Diffusion VAE for Phenotypic Drug Discovery
High-throughput phenotypic screens generate vast microscopy image datasets that push the limits of generative models due to their large dimensionality. Despite the growing popularity of general-purpos...
arxiv.org
October 30, 2025 at 4:22 PM
Excited to share our recent paper, ”Compressing Biology,” to be presented at the Imageomics workshop at NeurIPS 2025. 🔬💻 Work led by my amazing PhD student Télio Cropsal. #cellpainting #stablediffusion #imageomics
arxiv.org/abs/2510.19887
arxiv.org/abs/2510.19887
Reposted by Moritz Schauer
#AITHYRA, Vienna's new Biomedical AI institute, is hiring Postdocs!
Come work with us. Openings in: 🔹 Generative AI 🔹 Multimodal ML 🔹 Virology 🔹 Enzyme Function
Apply by Nov 20: oeaw.ac.at/aithyra/post... #PostDoc #AI #ML #Vienna #ScienceJobs
Come work with us. Openings in: 🔹 Generative AI 🔹 Multimodal ML 🔹 Virology 🔹 Enzyme Function
Apply by Nov 20: oeaw.ac.at/aithyra/post... #PostDoc #AI #ML #Vienna #ScienceJobs
October 20, 2025 at 3:46 PM
#AITHYRA, Vienna's new Biomedical AI institute, is hiring Postdocs!
Come work with us. Openings in: 🔹 Generative AI 🔹 Multimodal ML 🔹 Virology 🔹 Enzyme Function
Apply by Nov 20: oeaw.ac.at/aithyra/post... #PostDoc #AI #ML #Vienna #ScienceJobs
Come work with us. Openings in: 🔹 Generative AI 🔹 Multimodal ML 🔹 Virology 🔹 Enzyme Function
Apply by Nov 20: oeaw.ac.at/aithyra/post... #PostDoc #AI #ML #Vienna #ScienceJobs
Reposted by Moritz Schauer
Great first day of the 3rd annual CHAIR Structured Learning Workshop @ Chalmers! 🥳
Event page & agenda: ui.ungpd.com/Events/60bfc...
1st day featuring:
@betapata.bsky.social
@janstuehmer.bsky.social
@arnauddoucet.bsky.social
@frejohk.bsky.social
Event page & agenda: ui.ungpd.com/Events/60bfc...
1st day featuring:
@betapata.bsky.social
@janstuehmer.bsky.social
@arnauddoucet.bsky.social
@frejohk.bsky.social
October 28, 2025 at 10:47 PM
Great first day of the 3rd annual CHAIR Structured Learning Workshop @ Chalmers! 🥳
Event page & agenda: ui.ungpd.com/Events/60bfc...
1st day featuring:
@betapata.bsky.social
@janstuehmer.bsky.social
@arnauddoucet.bsky.social
@frejohk.bsky.social
Event page & agenda: ui.ungpd.com/Events/60bfc...
1st day featuring:
@betapata.bsky.social
@janstuehmer.bsky.social
@arnauddoucet.bsky.social
@frejohk.bsky.social
Very nice by Jun Otsuka @junotk.bsky.social and Hayato Saigo: link.springer.com/article/10.1...
about causal interventions/do calculus via string diagram surgery
about causal interventions/do calculus via string diagram surgery
September 17, 2025 at 2:04 PM
Very nice by Jun Otsuka @junotk.bsky.social and Hayato Saigo: link.springer.com/article/10.1...
about causal interventions/do calculus via string diagram surgery
about causal interventions/do calculus via string diagram surgery
Reposted by Moritz Schauer
Our process causation paper is published in Synthese! We propose that process causation (a la Salmon, Dowe, MDC new mechanists) can be modeled using a category-theoretic framework.
link.springer.com/article/10.1...
link.springer.com/article/10.1...
July 31, 2025 at 4:57 AM
Our process causation paper is published in Synthese! We propose that process causation (a la Salmon, Dowe, MDC new mechanists) can be modeled using a category-theoretic framework.
link.springer.com/article/10.1...
link.springer.com/article/10.1...
Confounding is just the failure of the Doob conditioning functor from a Markov category into the associated category of backward-forward optics to be lax comonoidal
September 11, 2025 at 1:12 PM
Confounding is just the failure of the Doob conditioning functor from a Markov category into the associated category of backward-forward optics to be lax comonoidal
Oh, hats up to Mike Hicks who authored a policy paragraph on double-blind reviewing and amphibious type systems for POPL 2013 which has stand the test of time and is used in ICSME, OOPSLA, ECOOP, SPLASH, ICFP, PLDI, POPL, CSF, CAV... pldi12.cs.purdue.edu/others/dbr-f...
These guidelines were originally created by Michael Hicks for POPL 2012, and slightly modified for PLDI 2012.
pldi12.cs.purdue.edu
September 4, 2025 at 8:33 AM
Oh, hats up to Mike Hicks who authored a policy paragraph on double-blind reviewing and amphibious type systems for POPL 2013 which has stand the test of time and is used in ICSME, OOPSLA, ECOOP, SPLASH, ICFP, PLDI, POPL, CSF, CAV... pldi12.cs.purdue.edu/others/dbr-f...
Reposted by Moritz Schauer
August 27, 2025 at 12:29 PM
"But I am conditioning on the outcome all the time and I think I understand the world just fine!"
Conditional on somebody being a more senior scholar active in replication initiatives, they are less likely to be known for their own highly visible scientific achievements.
In other news, conditioning on the outcome reliably makes it very hard to understand how the world works.
In other news, conditioning on the outcome reliably makes it very hard to understand how the world works.
It can be so frustrating to read STS research. Here are Bartscherer and Reinhart osf.io/rbyt6_v1/ Look at their flawed logic: Replication is *used as a career strategy*. The evidence? People were not known for earlier research. The clear confound? ECR’s drove the replication movement! 1/x
August 20, 2025 at 2:11 PM
"But I am conditioning on the outcome all the time and I think I understand the world just fine!"
Reposted by Moritz Schauer
2025 CHAIR Structured Learning Workshop -- Apply to attend: ui.ungpd.com/Events/60bfc...
May 6, 2025 at 10:02 AM
2025 CHAIR Structured Learning Workshop -- Apply to attend: ui.ungpd.com/Events/60bfc...
A golden Marburg Weidenhausen night accentuated by blue paper recycling bins…
August 8, 2025 at 7:19 PM
A golden Marburg Weidenhausen night accentuated by blue paper recycling bins…
So this is how I learned programming when I was twelve! 😃
July 14, 2025 at 5:15 PM
So this is how I learned programming when I was twelve! 😃
Reposted by Moritz Schauer
Are you passionate about AI for molecular engineering? Just two weeks left to apply to the 2 PhD positions currently open in our team at Chalmers! 🎓
For details: ailab.bio/join-us
For details: ailab.bio/join-us
🚨 We are currently recruiting 2 PhD students to join our team at Chalmers, which you can learn more about on our team website: ailab.bio/join-us
Details in thread below! (1/5)
Details in thread below! (1/5)
July 7, 2025 at 7:29 AM
Are you passionate about AI for molecular engineering? Just two weeks left to apply to the 2 PhD positions currently open in our team at Chalmers! 🎓
For details: ailab.bio/join-us
For details: ailab.bio/join-us
Reposted by Moritz Schauer
Please, please put your hyperparameter tuning procedure into the paper. For your method and the baselines
July 3, 2025 at 4:13 AM
Please, please put your hyperparameter tuning procedure into the paper. For your method and the baselines
Yeah Moritz, *electricity*, that’s totally why you were doing this (bridges for random walks on random graphs)
June 26, 2025 at 6:14 AM
Yeah Moritz, *electricity*, that’s totally why you were doing this (bridges for random walks on random graphs)
Reposted by Moritz Schauer
link 📈🤖
Parallel computations for Metropolis Markov chains with Picard maps (Grazzi, Zanella) We develop parallel algorithms for simulating zeroth-order (aka gradient-free) Metropolis Markov chains based on the Picard map. For Random Walk Metropolis Markov chains targeting log-concave distributio
Parallel computations for Metropolis Markov chains with Picard maps (Grazzi, Zanella) We develop parallel algorithms for simulating zeroth-order (aka gradient-free) Metropolis Markov chains based on the Picard map. For Random Walk Metropolis Markov chains targeting log-concave distributio
June 12, 2025 at 5:06 PM
link 📈🤖
Parallel computations for Metropolis Markov chains with Picard maps (Grazzi, Zanella) We develop parallel algorithms for simulating zeroth-order (aka gradient-free) Metropolis Markov chains based on the Picard map. For Random Walk Metropolis Markov chains targeting log-concave distributio
Parallel computations for Metropolis Markov chains with Picard maps (Grazzi, Zanella) We develop parallel algorithms for simulating zeroth-order (aka gradient-free) Metropolis Markov chains based on the Picard map. For Random Walk Metropolis Markov chains targeting log-concave distributio
Don’t let your idea of good wine be shaped by a generation you wouldn’t trust to choose the tiles for an underpass
June 20, 2025 at 8:15 AM
Don’t let your idea of good wine be shaped by a generation you wouldn’t trust to choose the tiles for an underpass
Tomorrow at #BayesComp @rseyer.bsky.social with arxiv.org/abs/2504.12190 (poster presentation, 19 Jun 2025, 5.30pm - 7.30pm local time)
June 18, 2025 at 7:30 AM
Tomorrow at #BayesComp @rseyer.bsky.social with arxiv.org/abs/2504.12190 (poster presentation, 19 Jun 2025, 5.30pm - 7.30pm local time)
It’s giving late-game vibes of Sid Meier’s Civilization, where the player is bored and just trying to see what happens if they declare some wars before they abandon the game.
June 17, 2025 at 4:56 PM
It’s giving late-game vibes of Sid Meier’s Civilization, where the player is bored and just trying to see what happens if they declare some wars before they abandon the game.
Reposted by Moritz Schauer
June 17, 2025 at 12:12 PM
Right, you don't need error bars on error bars.
Probabilistic uncertainty about uncertainty collapses. This is the “monadic join” in probability.
Instead of a coin with random bias p ∼ π, you can flip a coin with the deterministic bias μ.
Just take μ = E[p]. #statistics
Probabilistic uncertainty about uncertainty collapses. This is the “monadic join” in probability.
Instead of a coin with random bias p ∼ π, you can flip a coin with the deterministic bias μ.
Just take μ = E[p]. #statistics
June 17, 2025 at 10:01 AM
Right, you don't need error bars on error bars.
Probabilistic uncertainty about uncertainty collapses. This is the “monadic join” in probability.
Instead of a coin with random bias p ∼ π, you can flip a coin with the deterministic bias μ.
Just take μ = E[p]. #statistics
Probabilistic uncertainty about uncertainty collapses. This is the “monadic join” in probability.
Instead of a coin with random bias p ∼ π, you can flip a coin with the deterministic bias μ.
Just take μ = E[p]. #statistics
Reposted by Moritz Schauer
Here's how the gradient flow for minimizing KL(pi, target) looks under the Fisher-Rao metric. I thought some probability mass would be disappearing on the left and appearing on the right (i.e. teleportation), like a geodesic under the same metric, but I was very wrong... What's the right intuition?
June 13, 2025 at 4:29 PM
Here's how the gradient flow for minimizing KL(pi, target) looks under the Fisher-Rao metric. I thought some probability mass would be disappearing on the left and appearing on the right (i.e. teleportation), like a geodesic under the same metric, but I was very wrong... What's the right intuition?