
doi: 10.5281/zenodo.14930908 , 10.5281/zenodo.15131044 , 10.5281/zenodo.16333876 , 10.5281/zenodo.14032431 , 10.5281/zenodo.15532438 , 10.5281/zenodo.15128347 , 10.5281/zenodo.14033446 , 10.5281/zenodo.14267909 , 10.5281/zenodo.14987380 , 10.5281/zenodo.18816967 , 10.5281/zenodo.14177691 , 10.5281/zenodo.14166175 , 10.5281/zenodo.15128360 , 10.5281/zenodo.16219026 , 10.5281/zenodo.13879777 , 10.5281/zenodo.16411014 , 10.5281/zenodo.15978391 , 10.5281/zenodo.17372503 , 10.5281/zenodo.13884565 , 10.5281/zenodo.18007999 , 10.5281/zenodo.14611282 , 10.5281/zenodo.17378147 , 10.5281/zenodo.16218168 , 10.5281/zenodo.18721880 , 10.5281/zenodo.15130106 , 10.5281/zenodo.15131970 , 10.5281/zenodo.18375692 , 10.5281/zenodo.14284458 , 10.5281/zenodo.15130087 , 10.5281/zenodo.4603970 , 10.5281/zenodo.14824752 , 10.5281/zenodo.18927445
doi: 10.5281/zenodo.14930908 , 10.5281/zenodo.15131044 , 10.5281/zenodo.16333876 , 10.5281/zenodo.14032431 , 10.5281/zenodo.15532438 , 10.5281/zenodo.15128347 , 10.5281/zenodo.14033446 , 10.5281/zenodo.14267909 , 10.5281/zenodo.14987380 , 10.5281/zenodo.18816967 , 10.5281/zenodo.14177691 , 10.5281/zenodo.14166175 , 10.5281/zenodo.15128360 , 10.5281/zenodo.16219026 , 10.5281/zenodo.13879777 , 10.5281/zenodo.16411014 , 10.5281/zenodo.15978391 , 10.5281/zenodo.17372503 , 10.5281/zenodo.13884565 , 10.5281/zenodo.18007999 , 10.5281/zenodo.14611282 , 10.5281/zenodo.17378147 , 10.5281/zenodo.16218168 , 10.5281/zenodo.18721880 , 10.5281/zenodo.15130106 , 10.5281/zenodo.15131970 , 10.5281/zenodo.18375692 , 10.5281/zenodo.14284458 , 10.5281/zenodo.15130087 , 10.5281/zenodo.4603970 , 10.5281/zenodo.14824752 , 10.5281/zenodo.18927445
If you use this software, please cite it using the metadata from this file.
Bayesian Modeling and Probabilistic Programming in Python
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
