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1		-Dynamic Causal Modeling in Probabilistic Programming Languages (DCM-PPLs)
	1	+Dynamic Causal Modeling in Probabilistic Programming Languages

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10	10
11	11	)))
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13		-This open-source tool, called DCM_PPLs, was developed at INS in Marseille.
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15		-
	13	+This tool was developed at INS in Marseille.
16	16	Authors: Nina Baldy, Marmaduke Woodman, Viktor Jirsa, Meysam Hashemi
17	17
18	18
19		-The aim was to provide inference services for Dynamical Causal Modeling of Event-Related Potentials (ERPs) measured with EEG/MEG, using SATO Probabilistic Programming Languages (PPLs):
	17	+The aim is to provide inference services for Dynamical Causal Modeling of Event-Related Potentials (ERPs) measured with EEG/MEG, using SATO Probabilistic Programming Languages (PPLs):
20	20
21	21	Numpyro: [[https:~~/~~/num.pyro.ai/en/stable/>>url:https://num.pyro.ai/en/stable/]]
22	22
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26	26
27	27	Stan: [[https:~~/~~/mc-stan.org/>>url:https://mc-stan.org/]]
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29		-We have provided a taxonomy for model comparison tailored to algorithms: (1) adaptive Hamiltonian Monte Carlo, (2) automatic Laplace and (3) family of variational inference. We have provided solutions to address the deference by: 1) optimizing the hyperparameters, (2) leveraging initialization with prior information, (3) weighted stacking based on predictive accuracy.
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31		-
32		-Github: [[https:~~/~~/github.com/ins-amu/DCM_PPLs>>https://github.com/ins-amu/DCM_PPLs]]
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34		-
35	35	Notebooks:
36	36	\\[[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/DCM_ERP_NumPyro>>https://wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/DCM_ERP_NumPyro]]
37	37	\\Tutorial:
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39	39	[[https:~~/~~/wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/EITN_tutorial>>https://wiki.ebrains.eu/bin/view/Collabs/ebrains-task-3-3/Drive#notebooks/EITN_tutorial]]
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41		-
42		-{{{@article{DCM_PPLs,
43		-author = {Baldy, Nina and Woodman, Marmaduke and Jirsa, Viktor K. and Hashemi, Meysam},
44		-title = {Dynamic causal modelling in probabilistic programming languages},
45		-journal = {Journal of The Royal Society Interface},
46		-volume = {22},
47		-number = {227},
48		-pages = {20240880},
49		-year = {2025},
50		-doi = {10.1098/rsif.2024.0880},
	34	+{{{@article{Baldy2024AutoDCM,
	35	+ title={Dynamic Causal Modeling in Probabilistic Programming Languages},
	36	+ author={Baldy, Nina and Woodman, Marmaduke and Jirsa, Viktor and Hashemi, Meysam},
	37	+ journal={bioRxiv},
	38	+ pages={2024--11},
	39	+ year={2024},
	40	+ publisher={Cold Spring Harbor Laboratory}
51	51	}
52	52	}}}
53	53