Excited to share our new pre-print on bioRxiv, in which we reveal that feedback-driven motor corrections are encoded in small, previously missed neural signals.
07.04.2025 14:54 β π 26 π 16 π¬ 1 π 1
βModel-freeβ analysis of a complex system. Part II
Or: when you don't even see what your model is
The second part of the #ComplexityThoughts on βmodel-freeβ analysis of #ComplexSystems. As usual you have the:
Post: open.substack.com/pub/manlius/...
Podcast: creators.spotify.com/pod/show/com...
RSS: manlius.substack.com/feed
Enjoy! π
29.11.2024 17:10 β π 53 π 17 π¬ 5 π 2
Agreed. Not the best word choice from my side.
22.11.2024 09:31 β π 2 π 0 π¬ 0 π 0
Data-driven causal analysis of observational biological time series
Visualizations, simulations, and examples are used to provide an accessible synthesis of the reasoning and assumptions behind commonly used causal discovery approaches.
You can have a look at this paper. It touches on potential false-positives and false-negatives of CCM even for noiseless low-dimensional signals. It also shows how to circumvent them. There is a nice video walkthrough for the article. elifesciences.org/articles/72518
22.11.2024 00:53 β π 5 π 0 π¬ 2 π 0
Comp neuro @ Champalimaud
We're a neuroscience blog trying to make neuroscience accessible for everyone! Check it out here: https://neurofrontiers.blog
Professor of Neuromorphic Cognitive Systems at the University of Zurich and ETH Zurich, and director of the Institute of Neuroinformatics ( [β¦]
[bridged from https://fediscience.org/@giacomoi on the fediverse by https://fed.brid.gy/ ]
neuroscientist, free will denier
Postdoc at Helmholtz Munich (Schulz lab) and MPI for Biological Cybernetics (Dayan lab) || Ph.D. from EPFL (Gerstner lab) || Working on computational models of learning and decision-making in the brain; https://sites.google.com/view/modirsha
Cognitive Neuroscientist | Assistant Prof at VU Amsterdam | Active vision, memory, imagery | Multi-task studies, fMRI, eye tracking | https://matthiasnau.com
Machine Learning Professor
https://cims.nyu.edu/~andrewgw
Group Leader in TΓΌbingen, Germany
Iβm π«π· and I work on RL and lifelong learning. Mostly posting on ML related topics.
Studying how the brain develops
https://www.chinilab.com/
Community-maintained simulation-based inference (SBI) toolkit in PyTorch:
β’ NPE, NLE & NRE
β’ amortized and sequential inference
β’ wide range of diagnostics
Posts written by @deismic.bsky.social & @janboelts.bsky.social.
π https://github.com/sbi-dev/sbi
A CNRS/University Paris-Saclay group headed by Daniel Shulz at the Paris-Saclay Institute of Neuroscience. Where touch and motor control meet!
Neuroscientist and amateur pianist
Incoming assistant professor at Sorbonne University
Comp neuro postdoc @EPFL @KU_leuven ex-@Stanford | neural principles of efficient statistical inference | machine learning, biophysics, ephys & spike sorting, fMRI, psychoΟ
Researcher at CNRS & ENS working on the crossroads between machine learning and statistical physics.
Assistant Professor at the Machine Learning & Neural Computing department of the Donders Institute, Radboud University, Nijmegen, the Netherlands | Interested in brain-computer interfacing, neurotechnology, visual perception
Theoretical Neuroscientist | π Emergent neural population dynamics | Postdoc in Carandini-Harris lab at UCL | PhD from Gerstner lab at EPFL
https://tinyurl.com/yrxws43r
investigating electric waves in the brain,
thinking about visualization, interfaces,
art & beauty with computers.
nschawor.github.io
Frankfurt am Main, Germany
Lecturer at the University of Bristol.
probabilistic ML, optimisation, interpretability, LLM evals.
