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Sum-Product Networks

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17 March 2022


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Sum-Product Networks

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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

  • [Bueff2018]
    _Bueff, Andreas and Spelchert, Stefanie and Belle, Vaishak_
    **Tractable Querying and Learning in Hybrid Domains via Sum-Product Networks**
    preprint

  • [Butz2018a]
    _Butz, Cory J. and dos Santos André E. and Oliveira Jhonatan S. and Stavrinides John_
    **Efficient Examination of Soil Bacteria Using Probabilistic Graphical Models**
    International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems 2018

  • [Butz2018b]
    _Butz, Cory J. and Oliveira Jhonatan S. and dos Santos André E., Teixeira, A. L. and Poupart, P. and Kalra, A._
    **An Empirical Study of Methods for SPN Learning and Inference**
    PGM 2018

  • [Butz2019]
    _Butz, Cory J and Oliveira, Jhonatan S. and dos Santos, André E. and Teixeira, André L._
    **Deep Convolutional Sum-Product Networks**
    AAAI 2019

  • [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

  • [Choi2017]
    _Cheng, Arthur and Darwiche, Adnan_
    **On Relaxing Determinism in Arithmetic Circuits**
    ICML 2017

  • [Conaty2017]
    _Conaty, Diarmaid and Deratani Mauá, Denis and de Campos, Cassio P._
    **Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks**
    UAI 2017

  • [Conaty2018]
    _Conaty, Diarmaid and Del Rincon, Jesus Martinez and de Campos, Cassio P._
    **Cascading Sum-Product Networks using Robustness**
    PGM 2018

  • [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

  • [Dennis2017a]
    _Dennis, Aaron and Ventura, Dan_
    **Online Structure-Search for Sum-Product Networks**
    16th IEEE International Conference on Machine Learning and Applications (ICMLA) 2017

  • [Dennis2017b]
    _Dennis, Aaron and Ventura, Dan_
    **Autoencoder-Enhanced Sum-Product Networks**
    16th IEEE International Conference on Machine Learning and Applications (ICMLA) 2017

  • [Desana2016]
    _Desana, Mattia and Schn{\"{o}}rr Christoph_
    **Learning Arbitrary Sum-Product Network Leaves with Expectation-Maximization**
    arxiv.org/abs/1604.07243

  • [Desana2017]
    _Desana, Mattia and Schn{\"{o}}rr Christoph_
    **Sum-Product Graphical Models**
    arxiv.org/abs/1708.06438

  • [DiMauro2017]
    _Di Mauro, Nicola and Esposito, Floriana and Ventola, Fabrizio Giuseppe and Vergari, Antonio_
    **Alternative variable splitting methods to learn Sum-Product Networks**
    Proceedings of the 16th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2017)

  • [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

  • [Friesen2017]
    _Friesen, Abram L. and Domingos, Pedro_
    **Unifying Sum-Product Networks and Submodular Fields**
    Principled Approaches to Deep Learning Workshop at ICML 2017

  • [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

  • [Gens2017]
    _Gens, Robert and Domingos, Pedro_
    **Compositional Kernel Machines**
    ICLR 2017 - Workshop Track

  • [Hsu2017]
    _Hsu, Wilson and Kalra, Agastya and Poupart, Pascal_
    **Online Structure Learning for Sum-Product Networks with Gaussian Leaves**
    ICLR 2017 - Workshop Track

  • [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

  • [Jaini2018a]
    _Jaini, Priyank and Ghose Amur and Poupart, Pascal_
    **Prometheus: Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks**
    PGM 2018

    [Jaini2018b]
    Jaini, Priyank and Poupart, Pascal and Yu, Yaoliang
    Deep Homogeneous Mixture Models: Representation, Separation, and Approximation
    NIPS 2018</p>

  • [Joshi2018]
    _Joshi, Himanshu, Paul S. Rosenbloom, and Volkan Ustun_
    **Exact, Tractable Inference in the Sigma Cognitive Architecture via Sum-Product Networks**
    Advances in Cognitive Systems 6 (2018)

  • [Ko2018]
    _Ko, Ching-Yun and Chen, Cong and Zhang, Yuke and Batselier, Kim and Wong, Ngai_
    **Deep Compression of Sum-Product Networks on Tensor Networks**
    arXiv 2018

  • [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

  • [Mauà2017]
    _Mauá, Deratani Denis and Cozman Fabio Gagliardi and Conaty, Diarmaid and de Campos, Cassio P._
    **Credal Sum-Product Networks**
    ISIPTA 2017

  • [Mei2018]
    _Mei, Jun and Jiang, Yong and Tu, Kewei_
    **Maximum A Posteriori Inference in Sum-Product Networks**
    AAAI 2018

  • [Melibari2016a]
    _Melibari, Mazen and Poupart, Pascal and Doshi, Prashant_
    **Decision Sum-Product-Max Networks**
    Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI 2016)

  • [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

  • [Molina2017]
    _Molina, Alejandro and Natarajan, Sriraam and Kersting, Kristian_
    **Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions**
    Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI 2017)

  • [Molina2018]
    _Molina, Alejandro and Vergari, Antonio and Di Mauro, Nicola and Natarajan, Sriraam and Esposito, Floriana and Kersting, Kristian_
    **Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains**
    Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI 2018)

  • [Molina2019]
    _Molina, Alejandro and Vergari, Antonio and Stelzner, Karl and Peharz, Robert and Subramani, Pranav and Di Mauro, Nicola and Poupart, Pascal and Kersting, Kristian_
    **SPFlow: An Easy and Extensible Library for Deep Probabilistic Learning using Sum-Product Networks**
    arXiv:1901.03704

  • [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**
    Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI 2015)

  • [Nath2016]
    _Nath, Aniruddh and Domingos, Pedro_
    **Learning Tractable Probabilistic Models for Fault Localization**
    Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI 2016)

  • [Niepert2015]
    _Niepert, Mathias and Domingos, Pedro_
    **Learning and Inference in Tractable Probabilistic Knowledge Bases**
    UAI 2015

  • [Paris2020]
    _París, Iago and Sánchez-Cauce, Raquel and Díez, Francisco Javier_
    **Sum-product networks: A survey**
    arXiv:2004.01167

  • [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

  • [Peharz2019]
    _Robert Peharz and Antonio Vergari and Karl Stelzner and Alejandro Molina and Martin Trapp and Xiaoting Shao and Kristian Kersting and Zoubin Ghahramani_
    **Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning**
    UAI 2019

  • [Poon2011]
    _Poon, Hoifung and Domingos, Pedro_
    **Sum-Product Network: a New Deep Architecture**
    UAI 2011

  • [Pronobis2017a]
    _Pronobis, A. and Riccio, F. and Rao, R.~P.~N._
    **Deep Spatial Affordance Hierarchy: Spatial Knowledge Representation for Planning in Large-scale Environments**
    SSRR 2017

  • [Pronobis2017b]
    _Pronobis, A. and Ranganath, A. and Rao, R.~P.~N._
    **LibSPN: A Library for Learning and Inference with Sum-Product Networks and TensorFlow**
    Principled Approaches to Deep Learning Workshop at ICML 2017

  • [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

  • [Rashwan2018a]
    _Rashwan, Abdullah and Poupart, Pascal and Zhitang, Chen_
    **Discriminative Training of Sum-Product Networks by Extended Baum-Welch**
    PGM 2018

  • [Rashwan2018b]
    _Rashwan, Abdullah and Kalra, Agastya and Poupart, Pascal and Doshi, Prashant and Trimponias, George and Hsu, Wei-Shou_
    **Online Structure Learning for Feed-Forward and Recurrent Sum-Product Networks**
    NIPS 2018

  • [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

  • [Ratajczak2018]
    _Ratajczak, Martin and Tschiatschek, S and Pernkopf, F_
    **Sum-Product Networks for Sequence Labeling**
    preprint

  • [Rathke2017]
    _Rathke, F.; Desana, M. and Schnörr, C._
    **Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans**
    MICCAI 2017

  • [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

  • [Shao2019]
    _Shao, Xiaoting and Molina, Alejandro and Vergari, Antonio and Stelzner, Karl and Peharz, Robert and Liebig, Thomas and Kersting, Kristian_
    **Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures**
    arXiv:1905.08550

  • [Sharir2018]
    _Sharir, Or and Shashua, Amnon_
    ** Sum-Product-Quotient Networks**
    AISTATS 2018

  • [Sguerra2016]
    _Sguerra, Bruno Massoni and Cozman, Fabio G._
    **Image Classification Using Sum-Product Networks for Autonomous Flight of Micro Aerial Vehicles**
    BRACIS 2016 - 5th Brazilian Conference on Intelligent Systems

  • [Stelzner2019]
    _Stelzner, Karl and Peharz, Robert and Kersting, Kristian_
    **Faster Attend-Infer-Repeat with Tractable Probabilistic Models**
    ICML 2019

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

  • [Sommer2018]
    _Sommer, Lukas and Oppermann, Julian and Molina, Alejandro and Binnig, Carsten and Kersting, Kristian and Koch, Andreas_
    **Automatic Mapping of the Sum-Product Network Inference Problem to FPGA-Based Accelerators**
    ICCD 2018

  • [Tan2019]
    _Tan, Ping Liang, and Peharz, Robert_
    **Hierarchical Decompositional Mixtures of Variational Autoencoders**
    ICML 2019

  • [Trapp2016]
    _Trapp, Martin and Peharz, Robert and Skowron, Marcin and Madl, Tamas and Pernkopf, Franz and Trappl, Robert_
    **Structure Inference in Sum-Product Networks using Infinite Sum-Product Trees**
    Workshop on Practical Bayesian Nonparametrics at NIPS 2016

  • [Trapp2017]
    _Trapp, Martin and Madl, Tamas and Peharz, Robert and Pernkopf, Franz and Trappl, Robert_
    **Safe Semi-Supervised Learning of Sum-Product Networks**
    UAI 2017

  • [Trapp2018]
    _Trapp, Martin and Peharz, Robert and Rasmussen, Carl and Pernkopf, Franz_
    **Learning Deep Mixtures of Gaussian Process Experts Using Sum-Product Networks**
    Workshop on Tractable Probabilistic Models

  • [Trapp2019]
    _Trapp, Martin and Peharz, Robert and Ge, Hong and Pernkopf, Franz and Ghahramani, Zoubin_
    **Bayesian Learning of Sum-Product Networks**
    NeurIPS 2019

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

  • [Vergari2017]
    _Vergari, Antonio and Peharz, Robert and Di Mauro, Nicola and Esposito, Floriana_
    **Encoding and Decoding Representations with Sum- and Max-Product Networks**
    ICLR 2017 - Workshop Track

  • [Vergari2018a]
    _Vergari, Antonio and Peharz, Robert and Di Mauro, Nicola and Molina, Alejandro and Kersting, Kristian and Esposito, Floriana_
    **Sum-Product Autoencoding: Encoding and Decoding Representations with Sum-Product Networks**
    Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI 2018)

  • [Vergari2018b]
    _Vergari, Antonio and Di Mauro, Nicola and Esposito, Floriana_
    **Visualizing and Understanding Sum-Product Networks**
    Machine Learning Journal

  • [Vergari2019]
    _Vergari, Antonio and Molina, Alejandro and Peharz, Robert and Ghahramani, Zoubin and Kersting, Kristian and Valera, Isabel_
    **Automatic Bayesian Density Analysis**
    Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI 2019)

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

  • [Wolfshaar2019]
    _van de Wolfshaar, Jos and Pronobix, Andrzej_
    **Deep Convolutional Sum-Product Networks for Probabilistic Image Representations**
    arXiv:1902.06155

  • [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 and Gordon, Geoff_
    **A Unified Approach for Learning the Parameters of Sum-Product Networks**
    NIPS 2016

  • [Zhao2017]
    _Zhao, Han and Gordon, Geoff and Poupart, Pascal_
    **Efficient Computation of Moments in Sum-Product Networks**
    NIPS 2017

  • [Zheng2018]
    _Zheng, Kaiyu and Pronobis, Andrzej and Rao, Rajesh P.N._
    **Learning Graph-Structured Sum-Product Networks for Probabilistic Semantic Maps**
    AAAI 2018


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