jan-matthis

Research scientist @GoogleAI:

[Google AI @GoogleAI]

In collaboration with HHMI Janelia & Harvard, we introduce ZAPBench, a whole-brain activity dataset and benchmark with single cell resolution of a larval zebrafish, which will enable development and comparison of more accurate brain activity models. →https://t.co/4N6yvP2gki

[Michał Januszewski @michalj]

Can we predict future brain activity in a small vertebrate?🤔

We're releasing ZAPBench⚡️(#ICLR2025 spotlight): a benchmark to forecast activity in a whole vertebrate brain🧠 at single-cell resolution!🐟 70k+ neurons, 3 TB of data & extensive baselines. Connectome is coming!
🧵👇

[Thomas Kipf @tkipf]

Happy to announce a Student Researcher opportunity in our team @GoogleDeepMind in Mountain View, California ☀️

If you’re excited about foundational research on controllability of visual/3D generative models, please consider applying: https://t.co/uoImRfOK2T

[jan-matthis @janmatthis]

@ptrrupprecht @snsf_ch Congrats!

[Google AI @GoogleAI]

Introducing TensorStore, an open-source C++ and Python library designed for storage and manipulation of n-dimensional data, which can address key engineering challenges in scientific computing through better management and processing of large datasets. https://t.co/E8SvChpNPv

[jan-matthis @janmatthis]

I joined Google's Connectomics team as a research scientist in May -- very excited about the opportunities ahead!

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[jan-matthis @janmatthis]

A few weeks ago, I defended my PhD!

My thesis is now online: https://t.co/53iCX7GH1r

I am immensely grateful to @jakhmack, my fantastic co-authors, committee, and everyone who supported me on the way!

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[Machine Learning in Science @mackelab]

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
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[Machine Learning in Science @mackelab]

You like GANs, SBI, and the 100-yr anniversary of Jay Gatsby staring at a green light across the Long Island bay? Check out “GATSBI:Generative Adversarial Training for SBI” accepted at ICLR 2022! With @pramesh95 @janmatthis @janfiete @alvorithm @dvdgbg @ppjgoncalves @jakhmack 1/6

[ML⇌Science Colaboratory @mlcolab]

🪂 Now available! Slides + notebooks for our ongoing #SBI2021 workshop - content by @deismic_, @alvorithm, @janfiete, @janmatthis, @dvdgbg, @ppjgoncalves, reviewing and much help by @alpiges and Stefan Wezel.

@KyleCranmer @HeissenBergsUnc @glouppe @bkmi13 @ml4science @mackelab

[ML⇌Science Colaboratory @mlcolab]

Want to learn how to get more out of your simulator with machine learning? Apply now to become one of 20 participants of our 3-day, hands-on workshop on simulation-based inference! Sign up here! → https://t.co/YtW07W9HgH ←⏬

[Pyro @PyroAi]

Pyro 1.7 is released: PyTorch 1.9, biological sequence models, streaming MCMC for big models, AutoStructured guide, reparametrizer initialization, 3 tutorials, 8 distributions. Thanks Eli Weinstein @vitaliikl @nning_ola @mt_sokol @kamathhrishi @ordabayevy https://t.co/1qH9Mi03Zi

[jan-matthis @janmatthis]

@ogrisel @janfiete @dvdgbg @ppjgoncalves @jakhmack Thanks! Would be glad to chat more informally about this, just sent you a DM

[jan-matthis @janmatthis]

Attending #AISTATS2021?

I'll be presenting "Benchmarking Simulation-Based Inference" today at 16:30 CEST, come stop by!

Poster: https://t.co/nOLtIq1sv4
Paper: https://t.co/3UZiCNaiO2
Website: https://t.co/mEjQOUD7WA

Work with @janfiete, @dvdgbg, @ppjgoncalves and @jakhmack

[jan-matthis @janmatthis]

@ogrisel @janfiete @dvdgbg @ppjgoncalves @jakhmack Thanks a lot for the interest!

Just to be clear, I’ll be presenting the attached poster. We prepared a 3-minute video teaser, which I’ll put on https://t.co/Xt0XztMzcA after the conference.

Glad about any questions and comments!

[jan-matthis @janmatthis]

@Tkaraletsos :D same here!

[jan-matthis @janmatthis]

Almost what I said.. Found poetry in SlidesLive's automated captioning

[George Papamakarios @gpapamak]

The new and improved version of our review paper on normalizing flows is out!

Now published in the Journal of Machine Learning Research @JmlrOrg

https://t.co/8RNcwDUM1K

[Jakob Macke @jakhmack]

Multiple circuit settings of the🦞STG achieve the same network activity. But which of those⚙️ are energy efficient?

Find out at #Cosyne21 Poster 3-027 (a+b, 2-4pm + 9-11pm CET) by @deismic_ @ppjgoncalves!

https://t.co/KwIS9IkmVq

The answer will surprise you.

↗️ promoted

[Jakob Macke @jakhmack]

Simulation-based inference algorithms are useful to identify parameters of simulators from data. But there are so many approaches - how do they compare?

We made a benchmark!

With @janmatthis @janfiete @dvdgbg @ppjgoncalves

https://t.co/9YmzoqsDQZ
https://t.co/v6BDFmD9bL

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