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Scientific Reports
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April 27, 2019
Efficient message passing for cascade size distributions
Rebekka Burkholz
Physical Review. E
|
September 27, 2018
Correlations between thresholds and degrees: An analytic approach to model attacks and failure cascades
Rebekka Burkholz, Frank Schweitzer
Physical Review. E
|
May 16, 2018
Framework for cascade size calculations on random networks
Rebekka Burkholz, Frank Schweitzer
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence
|
December 17, 2024
Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently
Rebekka Burkholz, John Quackenbush
Glycobiology
|
June 30, 2021
Glycowork: A Python package for glycan data science and machine learning
Luc Thomès, Rebekka Burkholz, Daniel Bojar
Physical Review. E
|
May 14, 2016
How damage diversification can reduce systemic risk
Rebekka Burkholz, Antonios Garas, Frank Schweitzer
Cell Reports
|
June 16, 2021
Using graph convolutional neural networks to learn a representation for glycans
Rebekka Burkholz, John Quackenbush, Daniel Bojar
Scientific Reports
|
May 4, 2018
Explicit size distributions of failure cascades redefine systemic risk on finite networks
Rebekka Burkholz, Hans J Herrmann, Frank Schweitzer
Research Square
|
March 30, 2023
Biologically informed NeuralODEs for genome-wide regulatory dynamics
Intekhab Hossain, Viola Fanfani, John Quackenbush, et al.
Genome Biology
|
May 22, 2024
Biologically informed NeuralODEs for genome-wide regulatory dynamics
Intekhab Hossain, Viola Fanfani, Jonas Fischer, et al.
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Search research articles
Search
Showing results (1-10 of 20) with videos related to
Sort By:
Page
of 2
Scientific Reports
|
April 27, 2019
Efficient message passing for cascade size distributions
Rebekka Burkholz
Physical Review. E
|
September 27, 2018
Correlations between thresholds and degrees: An analytic approach to model attacks and failure cascades
Rebekka Burkholz, Frank Schweitzer
Physical Review. E
|
May 16, 2018
Framework for cascade size calculations on random networks
Rebekka Burkholz, Frank Schweitzer
Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence
|
December 17, 2024
Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently
Rebekka Burkholz, John Quackenbush
Glycobiology
|
June 30, 2021
Glycowork: A Python package for glycan data science and machine learning
Luc Thomès, Rebekka Burkholz, Daniel Bojar
Physical Review. E
|
May 14, 2016
How damage diversification can reduce systemic risk
Rebekka Burkholz, Antonios Garas, Frank Schweitzer
Cell Reports
|
June 16, 2021
Using graph convolutional neural networks to learn a representation for glycans
Rebekka Burkholz, John Quackenbush, Daniel Bojar
Scientific Reports
|
May 4, 2018
Explicit size distributions of failure cascades redefine systemic risk on finite networks
Rebekka Burkholz, Hans J Herrmann, Frank Schweitzer
Research Square
|
March 30, 2023
Biologically informed NeuralODEs for genome-wide regulatory dynamics
Intekhab Hossain, Viola Fanfani, John Quackenbush, et al.
Genome Biology
|
May 22, 2024
Biologically informed NeuralODEs for genome-wide regulatory dynamics
Intekhab Hossain, Viola Fanfani, Jonas Fischer, et al.
Page
of 2