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
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!
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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
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
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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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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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
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 ←⏬
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
@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!
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
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.
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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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