Mischa von Krause @mischavk

Joined November 2018

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Mischa von Krause @mischavk

3 years ago

Good news everyone - according to our new preprint, cognitive speed stays high throughout young and middle adulthood @MLSicorello @AnnaLSchubert @JeffRouder psyarxiv.com/3fx6u #BigData #BayesFlow

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Research lab of @al_zietlow @tudresden_de

#Perinatal #MentalHealth I #SocialInteraction I #EarlyChildhood I #ChildDevelopment I Family Mental Health

Child and Family Ment.. @zietlow_lab

362 Followers 402 Following Research lab of @al_zietlow @tudresden_de #Perinatal #MentalHealth I #SocialInteraction I #EarlyChildhood I #ChildDevelopment I Family Mental Health

Ph.D. candidate from the University of Heidelberg | M. Sc. Psychology | Interested in decision-making and statistical modeling

Nicola Schneider @nicola_schneide

2 Followers 27 Following Ph.D. candidate from the University of Heidelberg | M. Sc. Psychology | Interested in decision-making and statistical modeling

Postdoc at Heidelberg University. Individual Differences in Cognitive Control & WM; Psychometrics, Cognitive Modeling. R & Open Science. Musician.

Jean-Paul Snijder @jpsnijder

506 Followers 595 Following Postdoc at Heidelberg University. Individual Differences in Cognitive Control & WM; Psychometrics, Cognitive Modeling. R & Open Science. Musician.

Postdoc in Social Cognition and Decision Sciences @uni_tue
Interested in quantitative methods (Statistics, ML) & behavioral science (JDM, Rationality, AI)

Tobias R. Rebholz @TobiasRebholz

102 Followers 184 Following Postdoc in Social Cognition and Decision Sciences @uni_tue Interested in quantitative methods (Statistics, ML) & behavioral science (JDM, Rationality, AI)

Lukas Schumacher @LukasSchumach10

145 Followers 363 Following PhD Student @UniHeidelberg | Cognitive Modeling

Assistant professor at @RPI (deep learning, complex models, Bayesian stuff), collaborator with smart people, procrastinator, and occasional name-dropper.

Stefan Radev @StefanRadev13

147 Followers 122 Following Assistant professor at @RPI (deep learning, complex models, Bayesian stuff), collaborator with smart people, procrastinator, and occasional name-dropper.

Journalist | Lawyer. Views my own. Writes for public sector and government news site @TheMandarinAu. https://t.co/L4WkyU2kIF

Melissa Coade @Coadem

1K Followers 3K Following Journalist | Lawyer. Views my own. Writes for public sector and government news site @TheMandarinAu. https://t.co/L4WkyU2kIF

Researcher @zi_mannheim with focus on neurobiology of emotion (disorders). Also on Mastodon @mauriziosicorello@fediscience.org

Maurizio Sicorello @m.. @MLSicorello

639 Followers 531 Following Researcher @zi_mannheim with focus on neurobiology of emotion (disorders). Also on Mastodon @[email protected]

@annalschubert.bsky.social

Professor for Analysis and Modeling of Complex Data @uni_mainz. Interested in indiv. differences, neuroscience, and modeling.

Anna-Lena Schubert @AnnaLSchubert

2K Followers 849 Following @annalschubert.bsky.social Professor for Analysis and Modeling of Complex Data @uni_mainz. Interested in indiv. differences, neuroscience, and modeling.

Maurizio Sicorello @m.. @MLSicorello

639 Followers 531 Following Researcher @zi_mannheim with focus on neurobiology of emotion (disorders). Also on Mastodon @[email protected]

Anna-Lena Schubert @AnnaLSchubert

2K Followers 849 Following @annalschubert.bsky.social Professor for Analysis and Modeling of Complex Data @uni_mainz. Interested in indiv. differences, neuroscience, and modeling.

Stefan Radev @StefanRadev13

2 years ago

@janfiete @Antonino__Greco @janmatthis @_rdgao @jakhmack Specifically, here is a list of our work in the context of (cognitive) decision models: nature.com/articles/s4156… tqmp.org/RegularArticle… arxiv.org/abs/2005.03899 (3/3)

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@janfiete @Antonino__Greco @janmatthis @_rdgao @jakhmack I would like to point out a few major differences between BayesFlow and 2016 NPE: * fully amortized inference (training effort pays off after a few data sets) * accurate and flexible posteriors via cINNs * suitable summary networks deal easily with varying numbers of obs (1/3)

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Marco D @Marco_Daless

2 years ago

@janfiete @Antonino__Greco @janmatthis @_rdgao @jakhmack oh well, I would not say that BayesFlow has problems with re-training or varying trial length. In this paper peerj.com/articles/10316/, we applied it to a complex model for the Wisconsin Card Sorting Test, which is, you know, one of the most varying-trial-length tasks ever.