DeeProb-kit: a Python Library for Deep Probabilistic Modelling

8 December 2022

Papers citing "DeeProb-kit: a Python Library for Deep Probabilistic Modelling"

7 / 7 papers shown

Title
Scaling Up Probabilistic Circuits by Latent Variable Distillation Hoang Trung-Dung Honghua Zhang Guy Van den Broeck TPM 55 27 0 10 Oct 2022
Sum-Product Network Decompilation C. Butz Jhonatan de S. Oliveira Robert Peharz TPM 16 10 0 20 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 205 1,697 0 05 Dec 2019
SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks Alejandro Molina Antonio Vergari Karl Stelzner Robert Peharz P. Subramani Nicola Di Mauro Pascal Poupart Kristian Kersting TPM 36 60 0 11 Jan 2019
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 207 1,352 0 19 May 2017
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 266 3,696 0 26 May 2016
Sum-Product Networks: A New Deep Architecture Hoifung Poon Pedro M. Domingos TPM 81 758 0 14 Feb 2012