awesome-spn

A structured list of resources about Sum-Product Networks (SPNs)

Awesome Sum-Product Networks

awesome-spn is a curated and structured list of resources about Sum-Product Networks (SPNs), tractable deep density estimators.

This includes (even not formally published) research papers sorted by year and topics as well as links to tutorials and code and other related Tractable Probabilistic Models (TPMs). It is inspired by the SPN page at the Washington University.

Licence and Contributing

CC0

awesome-spn is released under Public Domain. Feel free to complete and/or correct any of these lists. Pull requests are very welcome!

Table of Contents

Papers

Sorted by year or topics

Year

2016

2015

2014

2013

2012

2011

Topics

Weight Learning

Structure Learning

Modeling

Applications

Theory

Related Works

Arithmetic Circuits

Other TPMs

Resources

Dataset

Code

Talks and Tutorials

References

  • [Adel2015]
    Adel, Tameem and Balduzzi, David and Ghodsi, Ali
    Learning the Structure of Sum-Product Networks via an SVD-based Algorithm
    Uncertainty in Artificial Intelligence 2015

  • [Amer2012]
    Amer, Mohamed and Todorovic, Sinisa
    Sum-Product Networks for Modeling Activities with Stochastic Structure
    2012 IEEE Conference on CVPR

  • [Amer2015]
    Amer, Mohamed and Todorovic, Sinisa
    Sum Product Networks for Activity Recognition
    IEEE Transactions on Pattern Analysis and Machine Intelligence

  • [Cheng2014]
    Cheng, Wei-Chen and Kok, Stanley and Pham, Hoai Vu and Chieu, Hai Leong and Chai, Kian Ming Adam
    Language modeling with Sum-Product Networks
    INTERSPEECH 2014

  • [Darwiche2003]
    Darwiche, Adnan
    A Differential Approach to Inference in Bayesian Networks
    Journal of the ACM 2003.

  • [Dellaleau2011]
    Delalleau, Olivier and Bengio, Yoshua
    Shallow vs. Deep Sum-Product Networks
    Advances in Neural Information Processing Systems 2011.

  • [Dennis2012]
    Dennis, Aaron and Ventura, Dan
    Learning the Architecture of Sum-Product Networks Using Clustering on Varibles
    Advances in Neural Information Processing Systems 25

  • [Dennis2015]
    Dennis, Aaron and Ventura, Dan
    Greedy Structure Search for Sum-product Networks
    International Joint Conference on Artificial Intelligence 2015

  • [Desana2016]
    Desana, Mattia and Schn{\“{o}}rr Christoph
    Expectation Maximization for Sum-Product Networks as Exponential Family
    arxiv.org/abs/1604.07243

  • [Friesen2015]
    Friesen, Abram L and Domingos, Pedro
    Recursive Decomposition for Nonconvex Optimization
    Proceedings of the 24th International Joint Conference on Artificial Intelligence

  • [Friesen2016]
    Friesen, Abram L and Domingos, Pedro
    The Sum-Product Theorem: A Foundation for Learning Tractable Models
    ICML 2016

  • [Gens2012]
    Gens, Robert and Domingos, Pedro
    Discriminative Learning of Sum-Product Networks
    NIPS 2012

  • [Gens2013]
    Gens, Robert and Domingos, Pedro
    Learning the Structure of Sum-Product Networks
    ICML 2013

  • [Jaini2016]
    Jaini, Priyank and Rashwan, Abdullah and Zhao, Han and Liu, Yue and Banijamali, Ershad and Chen, Zhitang and Poupart, Pascal
    Online Algorithms for Sum-Product Networks with Continuous Variables
    International Conference on Probabilistic Graphical Models 2016

  • [Krakovna2016]
    Krakovna, Viktoriya and Looks, Moshe
    A Minimalistic Approach to Sum-Product Network Learning for Real Applications
    ICLR 2016

  • [Lee2013]
    Lee, Sang-Woo and Heo, Min-Oh and Zhang, Byoung-Tak
    Online Incremental Structure Learning of Sum-Product Networks
    ICONIP 2013

  • [Lee2014]
    Lee, Sang-Woo and Watkins, Christopher and Zhang, Byoung-Tak
    Non-Parametric Bayesian Sum-Product Networks
    Workshop on Learning Tractable Probabilistic Models 2014

  • [Li2015]
    Weizhuo Li
    Combining sum-product network and noisy-or model for ontology matching
    Proceedings of the 10th International Workshop on Ontology Matching

  • [Livni2013]
    Livni, Roi and Shalev-Shwartz, Shai and Shamir, Ohad
    A Provably Efficient Algorithm for Training Deep Networks
    arXiv 2013

  • [Lowd2013]
    Lowd, Daniel and Rooshenas, Amirmohammad
    Learning Markov Networks With Arithmetic Circuits
    Proceedings of the 16th International Conference on Artificial Intelligence and Statistics 2013

  • [Martens2014]
    Martens, James and Medabalimi, Venkatesh
    On the Expressive Efficiency of Sum Product Networks
    arXiv/1411.7717

  • [Melibari2016a]
    Melibari, Mazen and Poupart, Pascal and Doshi, Prashant
    Decision Sum-Product-Max Networks
    Thirtieth AAAI Conference on Artificial Intelligence

  • [Melibari2016b]
    Melibari, Mazen and Poupart, Pascal and Doshi, Prashant
    Sum-Product-Max Networks for Tractable Decision Making
    Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems

  • [Melibari2016c]
    Melibari, Mazen and Poupart, Pascal and Doshi, Prashant and Trimponias, George
    Dynamic Sum-Product Networks for Tractable Inference on Sequence Data
    International Conference on Probabilistic Graphical Models 2016

  • [Nath2014]
    Nath, Aniruddh and Domingos, Pedro
    Learning Tractable Statistical Relational Models
    Workshop on Learning Tractable Probabilistic Models

  • [Nath2015]
    Nath, Aniruddh and Domingos, Pedro
    Learning Relational Sum-Product Networks
    AAAI 2015

  • [Nath2016]
    Nath, Aniruddh and Domingos, Pedro
    Learning Tractable Probabilistic Models for Fault Localization
    AAAI 2016

  • [Niepert2015]
    Niepert, Mathias and Domingos, Pedro
    Learning and Inference in Tractable Probabilistic Knowledge Bases
    UAI 2015

  • [Peharz2013]
    Peharz, Robert and Geiger, Bernhard and Pernkopf, Franz
    Greedy Part-Wise Learning of Sum-Product Networks
    ECML-PKDD 2013

  • [Peharz2014a]
    Peharz, Robert and Kapeller, Georg and Mowlaee, Pejman and Pernkopf, Franz
    Modeling Speech with Sum-Product Networks: Application to Bandwidth Extension
    ICASSP2014

  • [Peharz2014b]
    Robert Peharz and Gens, Robert and Domingos, Pedro
    Learning Selective Sum-Product Networks
    Workshop on Learning Tractable Probabilistic Models 2014

  • [Peharz2015a]
    Robert Peharz and Tschiatschek, Sebastian and Pernkopf, Franz and Domingos, Pedro
    On Theoretical Properties of Sum-Product Networks
    Proceedings of the 18th International Conference on Artificial Intelligence and Statistics

  • [Peharz2015b]
    Peharz, Robert
    Foundations of Sum-Product Networks for Probabilistic Modeling
    PhD Thesis

  • [Peharz2016]
    Robert Peharz and Robert Gens and Franz Pernkopf and Pedro Domingos
    On the Latent Variable Interpretation in Sum-Product Networks
    arxiv.org/abs/1601.06180

  • [Poon2011]
    Poon, Hoifung and Domingos, Pedro
    Sum-Product Network: a New Deep Architecture
    UAI 2011

  • [Rahman2016]
    Tahrima Rahman and Vibhav Gogate
    Merging Strategies for Sum-Product Networks: From Trees to Graphs
    UAI 2016

  • [Rashwan2016]
    Rashwan, Abdullah and Zhao, Han and Poupart, Pascal
    Online and Distributed Bayesian Moment Matching for Parameter Learning in Sum-Product Networks
    Proceedings of the 19th International Conference on Artificial Intelligence and Statistics

  • [Ratajczak2014]
    Ratajczak, Martin and Tschiatschek, S and Pernkopf, F
    Sum-Product Networks for Structured Prediction: Context-Specific Deep Conditional Random Fields
    Workshop on Learning Tractable Probabilistic Models 2014

  • [Rooshenas2014]
    Rooshenas, Amirmohammad and Lowd, Daniel
    Learning Sum-Product Networks with Direct and Indirect Variable Interactions
    ICML 2014

  • [Rooshenas2016]
    Rooshenas, Amirmohammad and Lowd, Daniel
    Discriminative Structure Learning of Arithmetic Circuits
    Proceedings of the 19th International Conference on Artificial Intelligence and Statistics

  • [Stuhlmueller2012]
    Stuhlmuller, Andreas and Goodman, Noah D.
    A Dynamic Programming Algorithm for Inference in Recursive Probabilistic Programs
    StaRAI 2012

  • [Vergari2015]
    Vergari, Antonio and Di Mauro, Nicola and Esposito, Floriana
    Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning
    ECML-PKDD 2015

  • [Vergari2016]
    Vergari, Antonio and Di Mauro, Nicola and Esposito, Floriana
    Visualizing and Understanding Sum-Product Networks
    arXiv:1608.08266

  • [Wang2015]
    Wang, Jinghua and Wang, Gang
    Hierarchical Spatial Sum-Product Networks for action recognition in Still Images
    arXiv:1511.05292

  • [Yuan2016]
    Zehuan Yuan and Hao Wang and Limin Wang and Tong Lu and Shivakumara Palaiahnakote and Chew Lim Tan
    Modeling Spatial Layout for Scene Image Understanding Via a Novel Multiscale Sum-Product Network
    Expert Systems with Applications

  • [Zhao2015]
    Zhao, Han and Melibari, Mazen and Poupart, Pascal
    On the Relationship between Sum-Product Networks and Bayesian Networks
    ICML 2015

  • [Zhao2016a]
    Zhao, Han and Adel, Tameem and Gordon, Geoff and Amos, Brandon
    Collapsed Variational Inference for Sum-Product Networks
    ICML 2016

  • [Zhao2016b]
    Zhao, Han and Poupart, Pascal
    A Unified Approach for Learning the Parameters of Sum-Product Networks
    NIPS 2016

Related Repositories

awesome-spn

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A structured list of resources about Sum-Product Networks (SPNs) ...


Top Contributors

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