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Jun Otsuka

@junotk.bsky.social
256 followers 32 following 39 posts

Philosopher of Science. The author of Thinking About Statistics (Routledge) and the Role of Mathematics in Evolutionary Theory (CUP). junotk.net

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Jun Otsuka @junotk.bsky.social · 15/09/2026
Just got a physical copy of Pim Edelaar's new book, the Selective Organism: and Expanded Theory of Adaptive Evolution. This is a truly wonderful book, applying causal methods to real eco-evo problems. And better yet, it is freely available: academic.oup.com/book/63165 Congrats, Pim!
academic.oup.com
The Selective Organism: An Expanded Theory of Adaptive Evolution
Abstract. Adaptive evolution is often described as natural selection acting on the genetic variation that affects ecological performance. This description
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Jun Otsuka @junotk.bsky.social · 29/07/2026
Nice paper by Fan Zhu who challenges the trialist (data/probability/causality) ontology I proposed in my book, Thinking About Statistics. link.springer.com/article/10.1...
link.springer.com
Beyond trialist ontology: a sketch of causal modeling hierarchy - Synthese
Jun Otsuka’s trialist ontology posits the causal model as a third-layer entity representing inter-world laws. This paper challenges Otsuka’s framework by focusing on a key yet overlooked element, abdu...
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Jun Otsuka @junotk.bsky.social · 24/06/2026
Really enjoyed giving a talk at the LMU Center for Advanced Studies, which is located in a lovely Munich neighborhood right in front of the house where Max Weber spent his later years. So excited to be staying here for the next month—no excuses for not being productive!
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Center for Advanced Studies @caslmu.bsky.social · 23/06/2026
Don't miss the #CASLunchTalk tomorrow! Jun Otsuka @junotk.bsky.social will talk about "Ontology and Symmetry of Statistical Models". @lmu-mcmp.bsky.social www.cas.lmu.de/en/events/ev...
cas.lmu.de
Lunch Talk: Ontology and Symmetry of Statistical Models
Prof. Jun Otsuka, Ph.D. (CAS Fellow/Zen University, Japan) | Chair: Dr. Tom Sterkenburg (CAS Young Center/LMU)
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Jun Otsuka @junotk.bsky.social · 25/05/2026
I'll visit the LMU Center for advanced studies from June 22 - July 17, and will give a talk on June 24. www.cas.lmu.de/en/events/ev...
cas.lmu.de
Lunch Talk: Ontology and Symmetry of Statistical Models
Prof. Jun Otsuka, Ph.D. (CAS Fellow/Zen University, Japan) | Chair: Dr. Tom Sterkenburg (CAS Young Center/LMU)
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PhilSci-Archive @philsci-archive.bsky.social · 20/05/2026
New on the Archive: Otsuka, Jun (2026) What Machine Learning Tells Us About the Mathematical Structure of Concepts. [Preprint] philsci-archive.pitt.edu/29712
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RD PascualMarqui @pascualmarqui.bsky.social · 01/05/2026
Causal Discovery of Synchronous Neural Oscillations based on Jacobian-informed VAR-LiNGAM Hiroshi Yokoyama, Ryosuke Takeuchi, Shohei Shimizu bioRxiv 2026.04.28.721377; doi: doi.org/10.64898/202...
The primary objective of system neuroscience is to understand the functional mapping and its causation in the dynamics of the brain network. Some experimental and methodological studies suggest that functional modularity and its hierarchical information processing in the brain network are crucial to understanding the functional role of task-specific or state-specific information flow in the brain. However, because most of the established techniques for detecting effective network structures in the neuroscience research field are strongly based on the ``Granger causality'' perspective, existing causal discovery methods specified for brain network analysis cannot identify the causal hierarchy in the modular network in the brain due to spurious correlation issues and indistinguishability of causal direction under the Gaussianity of observational noise in a linear system. To address the issues, we developed a causal discovery method for synchronous neural dynamics, called the Jacobian-informed linear non-Gaussian acyclic model, ``j-VAR-LiNGAM'', by incorporating the information of the Jacobian matrix determined from a phase-coupled oscillator model estimated from observed neural data into the VAR-LiNGAM algorithms. The method was validated by showing that it could extract causal ordering in both synthetic data and empirical neural observed data. Moreover, by analyzing the observed neural oscillatory signals obtained from mice and humans, we confirmed that our method identified causally hierarchical structures in the brain, which aligned with the neurophysiological interpretations. These findings suggested that our proposed method can reveal the neural basis of hierarchical information processing in the brain network.
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Jun Otsuka @junotk.bsky.social · 01/05/2026
My article "What does it mean to understand AI?" is out now in Harvard Data Science Review! I discuss mechanistic interpretability, representation engineering, world models, and Potemkin understanding from philosophical perspectives. hdsr.mitpress.mit.edu/pub/w1tfg5lx...
hdsr.mitpress.mit.edu
What Does It Mean to Understand AI?
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Jun Otsuka @junotk.bsky.social · 12/03/2026
On April 24, there is an online workshop featuring emerging young philosophers in the Asian region. My PhD student Soto Michida will give a talk entitled "A Deep Learning Perspective on Teleosemantics." He is doing fantastic work. Check it out! docs.google.com/document/d/1...
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Moritz Schauer @mschauer.bsky.social · 17/09/2025
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
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Jun Otsuka @junotk.bsky.social · 07/08/2025
"If you read only one book on the philosophy of statistics, make it this one. Otsuka’s compact yet comprehensive treatment (under 190 pages) provides a uniquely integrated view of the major statistical frameworks that shape modern data science and AI." crowintelligence.org/2025/03/19/s...
crowintelligence.org
Statistical Thinking as Philosophy: Essential Readings – Part I. - Crow Intelligence
"Philosophy of science without history of science is empty; history of science without philosophy of science is blind." — Imre Lakatos Statistics isn't just a collection of mathematical techniques—it'...
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Jun Otsuka @junotk.bsky.social · 31/07/2025
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...
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DB Krupp @dbkrupp.bsky.social · 25/07/2025
This is a very good book, and you can read it for free!
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Jun Otsuka @junotk.bsky.social · 25/07/2025
All titles of Cambridge Elements in the Philosophy of Biology, including mine The Role of Mathematics in Evolutionary Theory, are downloadable for free till the 25th. www.cambridge.org/core/element...
cambridge.org
The Role of Mathematics in Evolutionary Theory
Cambridge Core - Philosophy of Science - The Role of Mathematics in Evolutionary Theory
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Michela Massimi @michelamassimi.bsky.social · 21/06/2025
In Sendai where our fantastic host @junotk.bsky.social opens up the meeting of the Japanese Phil of Science Association (ita founding members include physicist Yukawa, I am told) and to these days includes lots of logicians and scientists alike. Excellent opening talk by @terumiyake.bsky.social
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Michela Massimi @michelamassimi.bsky.social · 22/06/2025
Packed day at the Japanese Phil Scie Association with brilliant talks by @junotk.bsky.social on rethinking the ontology associated with statistical models and Hanti Lin on realism and machine learning. Huge thanks to @junotk.bsky.social for stellar organisation and unrivalled hospitality. 💫
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Jun Otsuka @junotk.bsky.social · 22/06/2025
It was such a great honor to host Prof. Michela Massimi’s @michelamassimi.bsky.social special lecture at the Japanese Philosophy of Science Association. Her talk was truly inspiring for thinking about a more human-centered form of science—something much needed today.
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Michela Massimi @michelamassimi.bsky.social · 18/06/2025
A real joy to visit Taipei and to meet in person the incredible community of philosophers of science in South East Asia as well as hanging around with my old friend @sabinaleonelli.bsky.social and new colleagues too. Huge thanks to Karen Yan our wonderful host here 💫
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Yoshinari Yoshida @yoshinariyoshida.bsky.social · 13/06/2025
New article! Alan Love @mcps-philsci.bsky.social & I reflect on methodological & conceptual legacies of M. Abercrombie: quantitative measurement of cell behavior & concept of contact inhibition of locomotion. Published in @devbiol.bsky.social eur03.safelinks.protection.outlook.com?url=https%3A...
Methodological legacy: microcinematography combined with quantitative measurement. Conceptual legacy: contact inhibition of locomotion. Applicability and fecundity: neural crest cell migration, neuronal cell dispersion, and cancer invasion
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Jun Otsuka @junotk.bsky.social · 06/06/2025
New paper out in Royal Society Open Science! In this paper, we propose a novel Bayesian framework to model scientific practice as a whole, based on Taniguchi's theory of Collective Predictive Coding. (1/n) royalsocietypublishing.org/doi/10.1098/...
royalsocietypublishing.org
Collective predictive coding as model of science: formalizing scientific activities towards generative science | Royal Society Open Science
This article proposes a new conceptual framework called collective predictive coding as a model of science (CPC-MS) to formalize and understand scientific activities. Building on the idea of CPC originally developed to explain symbol emergence, CPC-MS ...
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Jun Otsuka @junotk.bsky.social · 20/05/2025
New preprint out! We use string diagrams to quantitatively model process causality (à la Salmon) and tackle issues like the Principle of Common Cause, explanatory irrelevance, and more—turns out process causation might be cooler than you thought. philsci-archive.pitt.edu/25367/
philsci-archive.pitt.edu
Modeling Causal Processes - PhilSci-Archive
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Yoshinari Yoshida @yoshinariyoshida.bsky.social · 25/04/2025
Officially published in EJPS! Alan Love @mcps-philsci.bsky.social and I discuss two forms of generalization: evolutionarily conserved mechanisms involving specific types of entities and abstract principles that are instantiated by heterogeneous entities #philsci link.springer.com/article/10.1...
The title page of the article: "Mechanisms and Principles: Two Approaches to Scientific Generalization," just published in European Journal for Philosophy of Science
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Jun Otsuka @junotk.bsky.social · 13/03/2025
Précis of Thinking About Statistics rdcu.be/edlaK URL to the article: link.springer.com/article/10.1...
rdcu.be
Précis of Thinking About Statistics
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SHIMIZU Shohei @sshimizu2006.bsky.social · 07/03/2025
www.riken.jp/en/careers/r...
riken.jp
Seeking Research Associates at RIKEN Center for Advanced Intelligence Project (W24325)
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Jun Otsuka @junotk.bsky.social · 06/03/2025
My book, Thinking About Statistics, got featured in Asian Journal of Philosophy! The book symposium hosts reviews by Elliott Sober, Jeanne Peijnenburg & David Atkinson, Hanti Lin, and Tung-Ying Wu, along with my reply. link.springer.com/collections/...
link.springer.com
Book Symposium: Thinking about Statistics (Jun Otsuka)
Jun Otsuka’s book Thinking about Statistics (Routledge, 2023 ) bridges the gap between statistics and philosophy. It does this by delineating the conceptual ...
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Jun Otsuka @junotk.bsky.social · 12/01/2025
Really enjoyed attending the Joint Mathematics Meetings special session on Categorical Generalizations of Conditionalization. We presented "a sheaf-theoretic reconstruction of statistical models", a joint work with Tatsuya Yoshii and Hayato Saigo.
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Peter Harrigan @peterwjharrigan.bsky.social · 30/12/2024
I enjoy the clarity of the work. It establishes the derivation of the statistical tools in a way that made the mathematics much clearer to me. I began to feel like I was reading mathematical formulae like english sentences - in the way that mathematics is a language.
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Peter Harrigan @peterwjharrigan.bsky.social · 29/12/2024
@junotk.bsky.social ‘s Thinking About Statistics is an absolute gem.
The cover of the book entitled Thinking About Statistics, The Philosophical Foundations by Prof Jun Otsuka. Published by Routledge
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Philosophy of Science Association @philsci.bsky.social · 19/12/2024
PSA Around the World 2025 🌍 Focus: Eastern & Central Europe. Call for Abstracts is now open! 🗓️ Deadline: March 31, 2025 💻 Fully online, Nov 6, 14, 22 $50 fee (waivers available). More info: www.philsci.org/psa_... 📄 Submit abstracts: psaatw25.sciencescon...
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Jun Otsuka @junotk.bsky.social · 27/10/2024
I’ll be speaking at the CIVICA DS Seminar on Oct 30! The registration link (below) lists an outdated title & abstract. The correct one is ‘Changing Ideals of Science in the Age of AI’, where I’ll discuss AI’s impact on what science should strive to be. socialdatascience.network/fall2024/ses...
socialdatascience.network
CIVICA Data Science Seminar Series
Session 2 Fall 2024: What does it mean to understand AI?
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Jun Otsuka @junotk.bsky.social · 11/07/2024
Forgot to share it here: a new paper coauthored with my student, where we solved the grue paradox using category-theoretic statistical modeling. www.journals.uchicago.edu/doi/10.1086/...
journals.uchicago.edu
A Categorical Solution to the Grue Paradox | The British Journal for the Philosophy of Science: Vol 0, No ja
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Jun Otsuka @junotk.bsky.social · 07/06/2024
Check out Elliott Sober's excellent review of my book. I'm truly honored! link.springer.com/article/10.1...
link.springer.com
Thoughts on Jun Otsuka’s Thinking about Statistics – the Philosphical Foundations - Asian Journal of Philosophy
Jun Otsuka’s excellent book, Thinking about Statistics - the Philosophical Foundations (Otsuka 2023) is mostly organized around the idea that different statistical approaches can be illuminated by lin...
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Jun Otsuka @junotk.bsky.social · 15/05/2024
I created a poster version synopsis of my book, 'Thinking About Statistics.' To be presented at JFFoS in Strasbourg next week.
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Jun Otsuka @junotk.bsky.social · 10/01/2024
Check out the synopsis of my book, 'Thinking About Statistics'! It's translated from the Japanese version using machine translation, so it may have some translation quirks, but should convey (some of) the main idea(s) of the book. philsci-archive.pitt.edu/22945/
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