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Alex Hess (he/him)

@alexjhess.bsky.social

450 followers 690 following 15 posts

doctoral student 👨‍🎓 in Computational Psychiatry at ETH Zurich | passionate about sports 🚴‍♂️🏒🏓🏋️🏂, food 🌮, causal inference ➡️⬅️, Bayesian stats 📊, and the brain 🧠

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Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

🚨 new paper 📄 🚨
I received an early christmas present this year - the publication of my first first-author paper from my PhD 🥳🎁
doi.org/10.3390/e261...
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Refining the Allostatic Self-Efficacy Theory of Fatigue and Depression Using Causal Inference

Allostatic self-efficacy (ASE) represents a computational theory of fatigue and depression. In brief, it postulates that (i) fatigue is a feeling state triggered by a metacognitive diagnosis of loss o...

doi.org

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Reposted by Alex Hess (he/him)

ETH Zurich @ethz.ch · Jul 9

A milestone for open AI: ETH Zurich and EPFL will release a fully open multilingual language model, trained on CSCS’s “Alps” supercomputer. Built for the public good, this model promotes transparency, inclusion, and innovation.

Read more:

A language model built for the public good

ETH Zurich and EPFL will release a large language model (LLM) developed on public infrastructure. Trained on the “Alps” supercomputer at the Swiss National Supercomputing Centre (CSCS), the new LLM ma...

ethz.ch

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Reposted by Alex Hess (he/him)

Tim Kietzmann @timkietzmann.bsky.social · Jul 8

Exciting new preprint from the lab: “Adopting a human developmental visual diet yields robust, shape-based AI vision”. A most wonderful case where brain inspiration massively improved AI solutions.

Work with @zejinlu.bsky.social @sushrutthorat.bsky.social and Radek Cichy

arxiv.org/abs/2507.03168

arxiv.org

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Reposted by Alex Hess (he/him)

danasmall.bsky.social @danasmall.bsky.social · Jun 11

For the past couple of years I met weekly with 3 amazing younger scientists @lilweb.bsky.social @debyee.bsky.social @rikepetzschner.bsky.social to share ideas and teach each other. No agenda. It was often the favorite part of my week. Then we started writing. www.sciencedirect.com/science/arti...

The interoceptive origin of reinforcement learning

Rewards play a crucial role in sculpting all motivated behavior. Traditionally, research on reinforcement learning has centered on how rewards guide l…

www.sciencedirect.com

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Reposted by Alex Hess (he/him)

Debbie Yee @debyee.bsky.social · Jun 11

Excited for our @rldmdublin2025.bsky.social workshop at the intersection of #NeuroAI and Aging. Tomorrow from 9 AM -1 PM in LTEE 3 in Hamilton Building, hope to see you there!

Representational Alignment and Aging at RLDM2025. Bridging the gap between socioemotional function in human and artificial intellgence

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Reposted by Alex Hess (he/him)

Katherine Stiles @katherinestiles.org · Jun 3

◽MedSky◽
For the first time, researchers have created genetically modified fruit flies that can become addicted to cocaine. The flies will self-administer cocaine if given the option.

How Cocaine Hijacks the Brain - Neuroscience News

In a groundbreaking study, researchers have engineered fruit flies that voluntarily consume cocaine, creating the first fly model for cocaine addiction.

neurosciencenews.com

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Reposted by Alex Hess (he/him)

Andrew Gelman et al. @statmodeling.bsky.social · Jun 1

Survey Statistics: it is the people
statmodeling.stat.columbia.edu/2025/06/01/s...

Survey Statistics: it is the people | Statistical Modeling, Causal Inference, and Social Science

statmodeling.stat.columbia.edu

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Reposted by Alex Hess (he/him)

The EuroCIM @eurocim.bsky.social · Apr 11

EuroCIM2025 came to an end! Thank you to all speakers, participants, and partners who made this year's conference a success. See you next year in Oxford!

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Reposted by Alex Hess (he/him)

Journal of Robustness Reports @robustnessreports.bsky.social · Apr 17

We are live!

Introducing the "Journal of Robustness Reports" – a Diamond Open-Access journal dedicated to publishing short reanalyses of empirical findings.

Check out our website and blog post about the journal:
🌐 scipost.org/JRobustRep
📄 www.bayesianspectacles.org/introducing-...

[Editorial: Introducing the Journal of Robustness Reports]

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Alex Hess (he/him) @alexjhess.bsky.social · Mar 25

A massive thank you to all my co-authors for their support and contributions, to our reviewers for their constructive feedback and to the Co-Eds-in-Chief @cpsyjournal.bsky.social, @xiaosigu.bsky.social and @drrickadams.bsky.social.
6/6

Bluesky

ms.bsky.social

Alex Hess (he/him) @alexjhess.bsky.social · Mar 25

Moreover, we argue that adopting Bayesian workflow for generative modelling helps increase the transparency and robustness of results, which is of fundamental importance for the long-term success of Computational Psychiatry.
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Alex Hess (he/him) @alexjhess.bsky.social · Mar 25

We show that harnessing information from two different data streams (binary choices + continuous response times) improves the accuracy of inference (specifically, identifiability of parameters and models).
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Alex Hess (he/him) @alexjhess.bsky.social · Mar 25

Our application example uses #HierarchicalGaussianFiltering (HGF). Next to highlighting the benefits of Bayesian workflow, we introduce multimodal response models in the #HGF framework which allow for simultaneous inference from multivariate data types.
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Graphical model representation of the HGF and example belief trajectories.

Alex Hess (he/him) @alexjhess.bsky.social · Mar 25

We present a worked example of #BayesianWorkflow in the context of a typical application scenario for #ComputationalPsychiatry. Bayesian workflow encompasses iterative model building, checking, validation, comparison and understanding.
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Flowchart of Bayesian workflow for generative modelling in Computational Psychiatry.

Alex Hess (he/him) @alexjhess.bsky.social · Mar 25

Are you new to the field of Computational Psychiatry or just looking for resources on applying Bayesian models of cognition to behavioural data? Then check out our new paper "Bayesian Workflow for Generative Modeling in Computational Psychiatry": doi.org/10.5334/cpsy...
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Bayesian Workflow for Generative Modeling in Computational Psychiatry | Computational Psychiatry

doi.org

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Reposted by Alex Hess (he/him)

Konrad Kording @kordinglab.bsky.social · Jan 21

Announcing a new week-long program for young computational neuroscience/ behavior professors to talk about rigorous science, mentoring, lab management, and networking in a stunning retreat setting. Do great science as a community and have fun doing so.

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Reposted by Alex Hess (he/him)

The Algonauts Project @algonautsproject.bsky.social · Jan 6

(1/4) The Algonauts Project 2025 challenge is now live!

Participate and build computational models that best predict how the human brain responds to multimodal movies!

Submission deadline: 13th of July.

#algonauts2025 #NeuroAI #CompNeuro #neuroscience #AI

algonautsproject.com

The Algonauts Project 2025

homepage

algonautsproject.com

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Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

I am grateful for the support of my fabulous co-authors Dina, Liv, Jakob and Klaas and look forward to build onto our findings in future work! Happy holidays & merry christmas everyone!🎄 n/n

Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

All of our analyses were prespecified (doi.org/10.5281/zeno...) and both data (doi.org/10.5281/zeno...) and analysis code (github.com/alexjhess/pb...) are openly available. 8/n

Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

Our study represents an initial attempt to refine and formalize ASE theory using methods from causal inference. Our results confirm key predictions from ASE theory but also suggest revisions which require empirical verification in future studies. 7/n

Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

Second, we confirmed the predicted negative average causal effect from metacognition of allostatic control (i.e. the feeling of being in control over one’s own body) to fatigue across different methods of estimation. 6/n

Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

We identified specific aspects of the proposed SCM that were inconsistent with the available data. This enabled formulation of an updated SCM that can be tested against future data. 5/n

Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

We converted ASE theory into a structural causal model (SCM). This allowed identification of empirically testable prespecified (!) hypotheses regarding causal relationships between the central variables of interest using questionnaire data from healthy volunteers. 4/n

Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

In this work, we focus on a recently emerging computational perspective on fatigue and depression, the allostatic self-efficacy theory (ASE; doi.org/10.3389/fnhu...). 3/n

Frontiers | Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression

This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depress...

doi.org

Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

What started as a small pet project as part of a course on causality taught by the inspiring Jonas Peters @ethzurich.bsky.social has now become a nice little piece of work summarising my first steps in the realm of causal inference. 2/n

Alex Hess (he/him) @alexjhess.bsky.social · Dec 23

🚨 new paper 📄 🚨
I received an early christmas present this year - the publication of my first first-author paper from my PhD 🥳🎁
doi.org/10.3390/e261...
1/n

Refining the Allostatic Self-Efficacy Theory of Fatigue and Depression Using Causal Inference

doi.org

2 2 9