Sebastian Bischoff
@sbischoff.bsky.social
PhD student @mackelab.bsky.social and claassenlab in Tübingen
Reposted by Sebastian Bischoff
Thrilled to announce we have three #NeurIPS2024 papers! Interested in simulating realistic neural data with diffusion models or recurrent neural networks, or in source distribution sorcery? Have a look 👇 1/4
December 9, 2024 at 7:28 PM
Thrilled to announce we have three #NeurIPS2024 papers! Interested in simulating realistic neural data with diffusion models or recurrent neural networks, or in source distribution sorcery? Have a look 👇 1/4
Reposted by Sebastian Bischoff
Watching the sbi-toolbox grow up, seeing its many uses on a wide range of applications, and experiencing the growth, momentum + team-spirit of the sbi community has been amazing. We now have a short software paper with many new contributions and contributors! So many thanks, and get involved!
The sbi package is growing into a community project 🌍 To reflect this and the many algorithms, neural nets, and diagnostics that have been added since its initial release, we have written a new software paper 📝 Check it out, and reach out if you want to get involved: arxiv.org/abs/2411.17337
sbi reloaded: a toolkit for simulation-based inference workflows
Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a significant challeng...
arxiv.org
November 27, 2024 at 11:44 AM
Watching the sbi-toolbox grow up, seeing its many uses on a wide range of applications, and experiencing the growth, momentum + team-spirit of the sbi community has been amazing. We now have a short software paper with many new contributions and contributors! So many thanks, and get involved!
Reposted by Sebastian Bischoff
@vetterj.bsky.social and I are excited to present our work at #NeurIPS2024! We present Sourcerer: a maximum-entropy, sample-based solution to source distribution estimation.
Paper: openreview.net/forum?id=0cg...
Code: github.com/mackelab/sou...
(1/8)
Paper: openreview.net/forum?id=0cg...
Code: github.com/mackelab/sou...
(1/8)
Sourcerer: Sample-based Maximum Entropy Source Distribution Estimation
Scientific modeling applications often require estimating a distribution of parameters consistent with a dataset of observations - an inference task also known as source distribution estimation....
openreview.net
December 10, 2024 at 2:29 AM
@vetterj.bsky.social and I are excited to present our work at #NeurIPS2024! We present Sourcerer: a maximum-entropy, sample-based solution to source distribution estimation.
Paper: openreview.net/forum?id=0cg...
Code: github.com/mackelab/sou...
(1/8)
Paper: openreview.net/forum?id=0cg...
Code: github.com/mackelab/sou...
(1/8)