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Pedro J. Goncalves

@ppjgoncalves.bsky.social

Computational Neuroscience and Machine Learning. Group Leader at VIB.AI (vib.ai/en) and Associate Professor at KU Leuven (www.kuleuven.be/english/kuleuven). Affiliated with VIB-KUL CN (vibneuroscienceleuven.be). More details at goncalveslab.sites.vib.be

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Mark D Humphries@markdhumphries.bsky.social · 2mo ago

The Group for Neural Theory is an enviable place to work. At the heart of Paris’s Left Bank, it’s a literal stone’s throw from the Pantheon And it has a remarkable training record On the occasion of its 20th birthday celebrations this week, here’s a further sample of its alumni… gnt20.github.io

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Luigi Acerbi@lacerbi.bsky.social · 4mo ago

1/ One of the issues of fully amortized inference / pretrained simulator-based inference is that you are stuck with the "prior" training distribution. What if you change your mind after training? In PriorGuide, one of our papers at ICLR this week, we allow the prior to be changed at runtime!

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Mark D Humphries@markdhumphries.bsky.social · 4mo ago

Job! My lab is hiring a pre-doctoral research assistant to work on the neural computations of foraging, seeking common cross-species algorithms. In collaboration with @brainapps.bsky.social & Nathan Lepora. Closes April 21st Pls share! jobs.nottingham.ac.uk/vacancy.aspx...

Job Vacancy at the University of Nottingham: Research Assistant (Fixed-term)

We seek a predoctoral research assistant to join the Humphries’ group at the University of Nottingham on a BBSRC-funded project to study the neural basis of foraging, in collaboration with the groups of Matthew Apps (Birmingham) and Nathan...

jobs.nottingham.ac.uk

Pedro J. Goncalves@ppjgoncalves.bsky.social · 5mo ago

Proud to see this fantastic work by my PhD student @anastasiakrouglova.bsky.social on multifidelity SBI out in the world!

Nastya Krouglova@anastasiakrouglova.bsky.social · 5mo ago

Our paper “Multifidelity Simulation-based Inference for Computationally Expensive Simulators” has been accepted at ICLR 2026! 🥳 We hope this can be a practical solution for anyone analysing and doing inference on computationally expensive simulators. Paper: openreview.net/pdf?id=bj0dc...

Machine Learning in Science@mackelab.bsky.social · 9mo ago

Simulation-based inference (SBI) has transformed parameter inference across a wide range of domains. To help practitioners get started and make the most of these methods, we joined forces with researchers from many institutions and wrote a practical guide to SBI. 📄 Paper: arxiv.org/abs/2508.12939

Simulation-Based Inference: A Practical Guide

A central challenge in many areas of science and engineering is to identify model parameters that are consistent with prior knowledge and empirical data. Bayesian inference offers a principled framewo...

arxiv.org

Tim Vogels@tpvogels.bsky.social · 10mo ago

“Mapping ion channel function” doi.org/10.7554/eLif... isn’t exactly a citation slayer, but it’s still one of my favourites (& my first independent project). Today we push pt 2, where we trace code origin & unite almost all channel models in a common expression. Boom! www.biorxiv.org/content/10.1...

An ion channel omnimodel for standardized biophysical neuron modelling

Biophysical neuron modeling is an indispensable tool in neuroscience research, with the combination of diverse ion channel kinetics and morphologies being used to explain various single-neuron propert...

biorxiv.org

sbi - Simulation-based inference@sbi-devs.bsky.social · 11mo ago

From hackathon to release: sbi v0.25 is here! 🎉 What happens when dozens of SBI researchers and practitioners collaborate for a week? New inference methods, new documentation, lots of new embedding networks, a bridge to pyro and a bridge between flow matching and score-based methods 🤯 1/7 🧵

Pedro J. Goncalves@ppjgoncalves.bsky.social · last yr.

Exciting project in Parkinson's disease! Patrik Verstreken's lab (verstrekenlab.sites.vib.be) and my lab are looking for a postdoc to develop and apply ML methods to the analysis of exciting brain-on-chip data. Please spread the word! More details at: jobs.vib.be/j/110908/pos...

Postdoc position: Computational methods for neurodegeneration research - VIB

About the labs The Verstreken Lab and the Gonçalves Lab are based in Leuven, Belgium and part of the

jobs.vib.be

NERF@nerflabs.bsky.social · last yr.

Hayden, Karthik & Nastya from the @ppjgoncalves.bsky.social lab joined the #SBI Hackathon in Tübingen in March, contributing to the open-source SBI package. Nastya gave a lightning talk on multifidelity inference for computationally expensive simulators. A great week of science & collaboration!

Auguste Schulz@auschulz.bsky.social · last yr.

Thanks so much for the shout-out, and congrats on your exciting work!! 🎉 🙂 Also, a good reminder to share that our work is now out in Cell Reports 🙏🎊 ⬇️ www.cell.com/cell-reports...

Modeling conditional distributions of neural and behavioral data with masked variational autoencoders

Schulz et al. demonstrate how neural encoding and decoding can be cast as computing conditional distributions and how to modify variational autoencoders (VAEs) to calculate such distributions. The pro...

cell.com

Cole Hurwitz@colehurwitz.bsky.social · last yr.

Current neurofoundation modeling approaches focus on either predicting neuronal responses (Wang et al. 2025) or behavior (POYO, POYO+, NDT2). Inspired by Schulz et al. 2025, we unify these two tasks using a multimodal masked modeling approach we call "Neural Encoding and Decoding at Scale (NEDS)"

Auguste Schulz@auschulz.bsky.social · last yr.

We apply our masked VAE approach to drosophila 🪰walking behavior, a macaque 🐒reach task & a synthetic dataset with access to the ground truth. We propose calibration checks to evaluate the models’ uncertainty estimates, to avoid making confidently wrong predictions. Check out the paper for more 🙂

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@psteinb.bsky.social · last yr.

It's been a blast, thanks to @sbi-devs.bsky.social ! This week's hackathon was phenomenal! 🙏 😍 The sbi hackathon welcomed about 25 people in Tübingen with contributions spanning the globe , e.g. 🇺🇸🇯🇵🇧🇪🇩🇪. Wanna see, what we did? Check out the PRs👇 github.com/sbi-dev/sbi/...

Pull requests · sbi-dev/sbi

sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you need fine-grained control or an easy-to-use interface, sbi has ...

github.com