Building interpretable models: From Bayesian networks to neural networks
(2016) Krakovna, Viktoriya
Url: https://dash.harvard.edu/handle/1/33840728
#my_bibtex #bayesian_network #machine_learning #neural_network #statistics #sum_product_networks
Building interpretable models: From Bayesian networks to neural networks
(2016) Krakovna, Viktoriya
Url: https://dash.harvard.edu/handle/1/33840728
#my_bibtex #bayesian_network #machine_learning #neural_network #statistics #sum_product_networks
Building interpretable models
(2016) : Krakovna, Viktoriya
url: https://dash.harvard.edu/handle/1/33840728
#neural_network #statistics #sum_product_networks #bayesian_network #machine_learning #my_bibtex
Building interpretable models
(2016) : Krakovna, Viktoriya
url: https://dash.harvard.edu/handle/1/33840728
#neural_network #sum_product_networks #bayesian_network #statistics #machine_learning #my_bibtex
Algorithms for Decision Making
(2022) : Mykel J. Kochenderfer and Tim A. Wheeler and Kyle H. Wray
url: https://algorithmsbook.com/
#MAS #__important #actor_critic_methods #algorithm #bayesian_network #belief #belief_propagation #decision_making #imit
#my_bibtex
Argumentation in Artificial Intelligence
(2009) : Rahwan, Iyad and Simari, Guillermo R.
DOI: https://doi.org/10.1007/978-0-387-98197-0
#ai #argumentation #bayesian_network #belief_revision #defeasible_logic #defeasible_reasoning #description_logic #d
#my_bibtex