Michael Deistler @deismic_
Machine Learning tools for neuroscience @MackeLab michaeldeistler.github.io Tübingen, Deutschland Joined February 2019-
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Neural networks are highly sensitive to tiny adversarial perturbations. Can we trust them to reliably perform Bayesian inference? We investigated the brittleness of inference networks & possible solutions. By @gloecklermanuel @deismic_ @jakhmack, accepted at ICML. 🧵1/5
We are hiring postdocs! If you're interested in working at the intersection of machine learning and neuroscience, join us in Tübingen @uni_tue to build biologically realistic and task-performing deep neural networks. Check out the full job ad here: mackelab.org/jobs/
Craziest day of sports for as long as I can remember.
Highly recommended!
Herzlichen Glückwunsch! Die Biologin Rita Triebskorn erhält den Tübinger Preis für #Wissenschaftskommunikation - Der Nachwuchspreis geht an die KI-Forscherin @SchulzAuguste: uni-tuebingen.de/universitaet/a… #Wisskomm #Biologie #KI
📢🧠Got your hands on one of the amazing connectomics data and want to use computational modeling to explore the underlying connectivity principles? Check out the recent preprint by @janfiete @HarthPhilipp @_rdgao @chhege M.Oberlaender @jakhmack et al. doi.org/10.1101/2023.0… 1/n
We (@lappalainenjk, @srinituraga + many others) built a neural network constrained by anatomical connectivity, and showed that--- with task-training---it develops realistic neural activity in single cells! This might be the most exciting study I have ever been part of.
We (@lappalainenjk, @srinituraga + many others) built a neural network constrained by anatomical connectivity, and showed that--- with task-training---it develops realistic neural activity in single cells! This might be the most exciting study I have ever been part of. https://t.co/SJJfmy4uUJ
How useful is a connectome? We show that you can predict quite a bit about the neural activity of a circuit from just measurements of its connectivity. Led by star graduate student @lappalainenjk, collaboration with @jakhmack. #connectome biorxiv.org/cgi/content/sh… 1/n
we know there is a diversity of cell types, network topographies, and other physiological mechanisms that shape network dynamics. can we include them all while automating fitting spiking networks to real brain data? Poster III-38 tonight at #cosyne23
explore our new work on how genes determine the physiology of neural cell types using #simultation based #inference with hybrid models, by my PhD student @YvesBernaerts with @ppjgoncalves @jakhmack @hippopedoid @__jnsbck__ @deismic_ @AndreasTolias 1/n biorxiv.org/content/10.110…
Super happy for Pedro! If you at e looking for a PhD position in ML and/or computational neuroscience, apply to his lab!
Super happy for Pedro! If you at e looking for a PhD position in ML and/or computational neuroscience, apply to his lab!
📣 Big news: @ppjgoncalves will be joining NERF as a new group leader this May! The Gonçalves lab will develop and apply #machinelearning methods to derive mechanistic insight in neuroscience. goncalveslab.sites.vib.be/en 1/3
How can we achieve sample-efficient exploration in object manipulation environments? Can we transfer experience from this intrinsic free-play phase to solve downstream tasks zero-shot? Find out in our #NeurIPS22 paper! With @_sebastianblaes and @GMartius 🧵1/6
Stoked to share my first #NeurIPS2022 paper. "Efficient Identification of informative features in SBI" arxiv.org/abs/2210.11915 w. @deismic_, @YvesBernaerts, @jakhmack, @CellTypist @ml4science We use NLE to efficiently identify how features constrain posteriors in SBI. (1/8)
Want to chat about simulation-based inference, normalizing flows, or ML for science? I’m in New Orleans, so DM me if you are around, or drop by my poster on Tuesday 11:00, Hall J, 717
Want to chat about simulation-based inference, normalizing flows, or ML for science? I’m in New Orleans, so DM me if you are around, or drop by my poster on Tuesday 11:00, Hall J, 717
How can one perform simulation-based inference on challenging real-world models? We introduce `Truncated Sequential Neural Posterior Estimation` (TSNPE), a robust and scalable simulation-based inference method. By @deismic_ @ppjgoncalves @jakhmack, accepted at NeurIPS ‘22. 🧵
📢 We just released a new sbi version with many improvements and several new features: a SNPE-method that avoids “leakage”, expected coverage tests, and embedding networks that allow iid data for SNPE 🧵 1/6
Wash your lobster costumes cause it’s time to party! 🥳🦞 I’m super happy that this is in print now! A huge "thank you" to my amazing colleagues and supervisors who provided scientific and mental support during this journey! 💝
Wash your lobster costumes cause it’s time to party! 🥳🦞 I’m super happy that this is in print now! A huge "thank you" to my amazing colleagues and supervisors who provided scientific and mental support during this journey! 💝 https://t.co/zLaaOPt4aZ
📢We released a new version of SBI with many improvements and one highlight🎉: We enabled access to ArviZ (@arviz_devs) to benefit from their amazing MCMC diagnostics and inference visualizations 🤩 (thanks to @sethaxen)! see github.com/mackelab/sbi/r… for details 1/2
Simulation-based inference (SBI) has accelerated model-building across many disciplines. It’s also useful for studying cognition: We present Mixed Neural Likelihood Estimation, an SBI method tailored to models of decision-making! By @janfiete @janmatthis @_rdgao @jakhmack 1/5
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Happy to share our new preprint “Probabilistic Inference on Virtual Brain Models of Disorders” with @sci_developer (A. Ziaee-Mehr, equal contribution), Marmaduke Woodman, @spase_petkoski & @ViktorJirsa. biorxiv.org/content/10.110…
Happy to announce that @memming and me have put together a workshop on reconstructing dynamical systems from neural data with a fantastic line-up of speakers… more details to come. Join us in Cascais!
#Cosyne2024 workshops have been announced!!🤓🧠🤩 Check them out 👇👇👇 cosyne.org/workshops-prog…
What does this dog have to do with a sh!tty data project? In the scope of the Data Literacy course, two of our students Michelle Schlicher and Karsten Binz analyzed as a real-world problem whether there is a connection between the meals of their dog Buddy and his diarrhea. (1/8)
#AutoML23 social chairs enjoying the social program in a chair @automl_conf. With @__mfeurer__
See our new work using #SBI and #TVB to investigate the causal mechanisms underlying diaschisis 🥳🥳 Well done @GRabuffo, @sci_developer, et al and thanks to all our global contributors! 👏 👏
Focal brain manipulations can induce both local and nonlocal effects, a phenomenon also known as diaschisis. What are the underlying neurophysiological mechanisms? We addressed this question with mouse experiments and virtual brain models. biorxiv.org/content/10.110… Tread 👇
Thrilled to receive the Best Student Paper Award at the Epistemic Uncertainty Workshop at #UAI2023 🤩 If you haven't read about our efforts to equip pretrained models with uncertainty estimates, we're continuously updating our benchmark 👉 arxiv.org/abs/2307.03810
📢New work on estimating uncertainty in MR recon. We developed a method based on conditional VAEs that produces fast, well-calibrated uncertainty estimates. We further show how uncertainties can be *propagated* to a downstream segmentation task. ➡️Check out @95pfischer's thread!
Accelerating MR scans introduces uncertainty. But what can you do with it once you have it? In our @UNSURE_Workshop work we take a holistic look at uncertainty estimation and propagation to downstream clinical tasks. 📜arxiv.org/abs/2308.02631 🔗github.com/paulkogni/MR-R…
Accelerating MR scans introduces uncertainty. But what can you do with it once you have it? In our @UNSURE_Workshop work we take a holistic look at uncertainty estimation and propagation to downstream clinical tasks. 📜arxiv.org/abs/2308.02631 🔗github.com/paulkogni/MR-R…
Last week, I successfully defended my PhD! 🥳🎉🥂 I want to thank everyone that supported me on this journey, especially Ingo Steinwart, @BachFrancis, @ViktorZaverkin, @SimTechStuttga2. Looking forward to a new postdoc adventure with @BachFrancis and @GaelVaroquaux!
Have you ever thought that the classification of El Niño events into EP and CP is rather arbitrary? Our new study challenges these binary classifications using a fuzzy unsupervised approach. #ENSO Preprint: arxiv.org/abs/2307.11552
@neuralreckoning @jmourabarbosa Remarkable that people still don't join the dots 20 years on... idp.nature.com/authorize/casa…
Happy to share a jax library for conditional normalizing flows LFIAX (Likelihood Free Inference in jAX). In addition to conditional normalizing flows, this has some Bayesian optimal experimental design goodies. github.com/vz415/lfiax
@ArnaudDelaunoy and I are presenting our poster about the balance criterion for simulation-based inference at @aabi_org today at 1450! x.com/arnauddelaunoy…
Balancing has empirically proven to produce more conservative posterior approximations. However, this technique was limited to ratio-based algorithms. This work extends its applicability to all methods that provide posterior density estimation. arxiv.org/abs/2304.10978
Happy that my master's thesis paper is finally published! journals.plos.org/ploscompbiol/a… Thanks to all co-authors and especially to my first neuroscience mentors @ComputingCajal & @jedlickap who introduced me to the field and motivated me to continue my journey after graduation!
Do apply! Fantastic projects within an awesome community!
Our 2024 PhD Call is now open! Join us for exciting research in: 🧠 Neural circuits & behavior 🧠 Neural systems and computation 🧠 Advanced brain recording and imaging Please spread the word and send curious students our way! nerfphdcall.sites.vib.be
Delighted that #BUCTD has been accepted at #ICCV! 🙌📚 Grateful for the exceptional teamwork and dedication of @zhoumu53, @TrackingActions, and @TrackingPlumes!
🍾 Super happy to say that #BUCTD was accepted to #ICCV2023! Huge congratulations to @zhoumu53, @LStoffl & @TrackingPlumes, it was so great to work with you all🙏🎉 🥂 🇨🇭@EPFL_en @Brainmind_EPFL @ICepfl @epflSV ⬇️ Details below!
I was watching Lord of the Rings last night and realized there are many parallels with academia! A thread 🧵👇
🗣️ Today I had the pleasure to present our ongoing work @netsci2023, in Vienna. 🎯 I talked about an approach to perform inference on heterogeneous and attributed multilayer networks. ♻️ Stay tuned for details!
JOB AD, please share: The Groschner lab @TheCrick is looking for a #postdoc to study temporal signal processing in the #Drosophila #brain. crick.wd3.myworkdayjobs.com/External/job/L…