Variational autoencoder (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Variational autoencoder" in English language version.

refsWebsite

Global rank English rank

18arxiv.org

69^th place

59^th place

9doi.org

2^nd place

6semanticscholar.org

11^th place

8^th place

4nih.gov

4^th place

3worldcat.org

5^th place

2mlr.press

low place

2harvard.edu

18^th place

17^th place

2openreview.net

low place

1books.google.com

3^rd place

1thecvf.com

low place

1aaai.org

9,352^nd place

5,696^th place

1mit.edu

415^th place

327^th place

1lilianweng.github.io

low place

1neurips.cc

low place

1sciencedirect.com

149^th place

178^th place

aaai.org (Global: 9,352^nd place; English: 5,696^th place)

ojs.aaai.org

Xu, Weidi; Sun, Haoze; Deng, Chao; Tan, Ying (2017-02-12). "Variational Autoencoder for Semi-Supervised Text Classification". Proceedings of the AAAI Conference on Artificial Intelligence. 31 (1). doi:10.1609/aaai.v31i1.10966. S2CID 2060721.

arxiv.org (Global: 69^th place; English: 59^th place)

Kingma, Diederik P.; Welling, Max (2022-12-10). "Auto-Encoding Variational Bayes". arXiv:1312.6114 [stat.ML].
Dilokthanakul, Nat; Mediano, Pedro A. M.; Garnelo, Marta; Lee, Matthew C. H.; Salimbeni, Hugh; Arulkumaran, Kai; Shanahan, Murray (2017-01-13). "Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders". arXiv:1611.02648 [cs.LG].
Hsu, Wei-Ning; Zhang, Yu; Glass, James (December 2017). "Unsupervised domain adaptation for robust speech recognition via variational autoencoder-based data augmentation". 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU). pp. 16–23. arXiv:1707.06265. doi:10.1109/ASRU.2017.8268911. ISBN 978-1-5090-4788-8. S2CID 22681625.
Kingma, Diederik P.; Welling, Max (2013-12-20). "Auto-Encoding Variational Bayes". arXiv:1312.6114 [stat.ML].
Rezende, Danilo Jimenez; Mohamed, Shakir; Wierstra, Daan (2014-06-18). "Stochastic Backpropagation and Approximate Inference in Deep Generative Models". International Conference on Machine Learning. PMLR: 1278–1286. arXiv:1401.4082.
Bengio, Yoshua; Courville, Aaron; Vincent, Pascal (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. Bibcode:2013ITPAM..35.1798B. doi:10.1109/TPAMI.2013.50. ISSN 1939-3539. PMID 23787338. S2CID 393948.
Kingma, Diederik P.; Rezende, Danilo J.; Mohamed, Shakir; Welling, Max (2014-10-31). "Semi-Supervised Learning with Deep Generative Models". arXiv:1406.5298 [cs.LG].
Burgess, Christopher P.; Higgins, Irina; Pal, Arka; Matthey, Loic; Watters, Nick; Desjardins, Guillaume; Lerchner, Alexander (2018-04-10). "Understanding disentangling in β-VAE". arXiv:1804.03599 [stat.ML].
Dai, Bin; Wipf, David (2019-10-30). "Diagnosing and Enhancing VAE Models". arXiv:1903.05789 [cs.LG].
Dorta, Garoe; Vicente, Sara; Agapito, Lourdes; Campbell, Neill D. F.; Simpson, Ivor (2018-07-31). "Training VAEs Under Structured Residuals". arXiv:1804.01050 [stat.ML].
Larsen, Anders Boesen Lindbo; Sønderby, Søren Kaae; Larochelle, Hugo; Winther, Ole (2016-06-11). "Autoencoding beyond pixels using a learned similarity metric". International Conference on Machine Learning. PMLR: 1558–1566. arXiv:1512.09300.
Bao, Jianmin; Chen, Dong; Wen, Fang; Li, Houqiang; Hua, Gang (2017). "CVAE-GAN: Fine-Grained Image Generation Through Asymmetric Training". pp. 2745–2754. arXiv:1703.10155 [cs.CV].
Drefs, J.; Guiraud, E.; Panagiotou, F.; Lücke, J. (2023). "Direct evolutionary optimization of variational autoencoders with binary latents". Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Lecture Notes in Computer Science. Vol. 13715. Springer Nature Switzerland. pp. 357–372. arXiv:2011.13704. doi:10.1007/978-3-031-26409-2_22. ISBN 978-3-031-26408-5.
Kingma, Diederik P.; Welling, Max (2022-12-10). "Auto-Encoding Variational Bayes". arXiv:1312.6114 [stat.ML].
Turinici, Gabriel (2021). "Radon-Sobolev Variational Auto-Encoders". Neural Networks. 141: 294–305. arXiv:1911.13135. doi:10.1016/j.neunet.2021.04.018. ISSN 0893-6080. PMID 33933889.
Gretton, A.; Li, Y.; Swersky, K.; Zemel, R.; Turner, R. (2017). "A Polya Contagion Model for Networks". IEEE Transactions on Control of Network Systems. 5 (4): 1998–2010. arXiv:1705.02239. doi:10.1109/TCNS.2017.2781467.
Tolstikhin, I.; Bousquet, O.; Gelly, S.; Schölkopf, B. (2018). "Wasserstein Auto-Encoders". arXiv:1711.01558 [stat.ML].
Louizos, C.; Shi, X.; Swersky, K.; Li, Y.; Welling, M. (2019). "Kernelized Variational Autoencoders". arXiv:1901.02401 [astro-ph.CO].

books.google.com (Global: 3^rd place; English: 3^rd place)

Pinheiro Cinelli, Lucas; et al. (2021). "Variational Autoencoder". Variational Methods for Machine Learning with Applications to Deep Networks. Springer. pp. 111–149. doi:10.1007/978-3-030-70679-1_5. ISBN 978-3-030-70681-4. S2CID 240802776.

doi.org (Global: 2^nd place; English: 2^nd place)

Pinheiro Cinelli, Lucas; et al. (2021). "Variational Autoencoder". Variational Methods for Machine Learning with Applications to Deep Networks. Springer. pp. 111–149. doi:10.1007/978-3-030-70679-1_5. ISBN 978-3-030-70681-4. S2CID 240802776.
Hsu, Wei-Ning; Zhang, Yu; Glass, James (December 2017). "Unsupervised domain adaptation for robust speech recognition via variational autoencoder-based data augmentation". 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU). pp. 16–23. arXiv:1707.06265. doi:10.1109/ASRU.2017.8268911. ISBN 978-1-5090-4788-8. S2CID 22681625.
Xu, Weidi; Sun, Haoze; Deng, Chao; Tan, Ying (2017-02-12). "Variational Autoencoder for Semi-Supervised Text Classification". Proceedings of the AAAI Conference on Artificial Intelligence. 31 (1). doi:10.1609/aaai.v31i1.10966. S2CID 2060721.
Kameoka, Hirokazu; Li, Li; Inoue, Shota; Makino, Shoji (2019-09-01). "Supervised Determined Source Separation with Multichannel Variational Autoencoder". Neural Computation. 31 (9): 1891–1914. doi:10.1162/neco_a_01217. PMID 31335290. S2CID 198168155.
Bengio, Yoshua; Courville, Aaron; Vincent, Pascal (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. Bibcode:2013ITPAM..35.1798B. doi:10.1109/TPAMI.2013.50. ISSN 1939-3539. PMID 23787338. S2CID 393948.
Gao, Rui; Hou, Xingsong; Qin, Jie; Chen, Jiaxin; Liu, Li; Zhu, Fan; Zhang, Zhao; Shao, Ling (2020). "Zero-VAE-GAN: Generating Unseen Features for Generalized and Transductive Zero-Shot Learning". IEEE Transactions on Image Processing. 29: 3665–3680. Bibcode:2020ITIP...29.3665G. doi:10.1109/TIP.2020.2964429. ISSN 1941-0042. PMID 31940538. S2CID 210334032.
Drefs, J.; Guiraud, E.; Panagiotou, F.; Lücke, J. (2023). "Direct evolutionary optimization of variational autoencoders with binary latents". Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Lecture Notes in Computer Science. Vol. 13715. Springer Nature Switzerland. pp. 357–372. arXiv:2011.13704. doi:10.1007/978-3-031-26409-2_22. ISBN 978-3-031-26408-5.
Turinici, Gabriel (2021). "Radon-Sobolev Variational Auto-Encoders". Neural Networks. 141: 294–305. arXiv:1911.13135. doi:10.1016/j.neunet.2021.04.018. ISSN 0893-6080. PMID 33933889.
Gretton, A.; Li, Y.; Swersky, K.; Zemel, R.; Turner, R. (2017). "A Polya Contagion Model for Networks". IEEE Transactions on Control of Network Systems. 5 (4): 1998–2010. arXiv:1705.02239. doi:10.1109/TCNS.2017.2781467.

harvard.edu (Global: 18^th place; English: 17^th place)

ui.adsabs.harvard.edu

Bengio, Yoshua; Courville, Aaron; Vincent, Pascal (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. Bibcode:2013ITPAM..35.1798B. doi:10.1109/TPAMI.2013.50. ISSN 1939-3539. PMID 23787338. S2CID 393948.
Gao, Rui; Hou, Xingsong; Qin, Jie; Chen, Jiaxin; Liu, Li; Zhu, Fan; Zhang, Zhao; Shao, Ling (2020). "Zero-VAE-GAN: Generating Unseen Features for Generalized and Transductive Zero-Shot Learning". IEEE Transactions on Image Processing. 29: 3665–3680. Bibcode:2020ITIP...29.3665G. doi:10.1109/TIP.2020.2964429. ISSN 1941-0042. PMID 31940538. S2CID 210334032.

lilianweng.github.io (Global: low place; English: low place)

"From Autoencoder to Beta-VAE". Lil'Log. 2018-08-12.

mit.edu (Global: 415^th place; English: 327^th place)

direct.mit.edu

Kameoka, Hirokazu; Li, Li; Inoue, Shota; Makino, Shoji (2019-09-01). "Supervised Determined Source Separation with Multichannel Variational Autoencoder". Neural Computation. 31 (9): 1891–1914. doi:10.1162/neco_a_01217. PMID 31335290. S2CID 198168155.

mlr.press (Global: low place; English: low place)

proceedings.mlr.press

Rezende, Danilo Jimenez; Mohamed, Shakir; Wierstra, Daan (2014-06-18). "Stochastic Backpropagation and Approximate Inference in Deep Generative Models". International Conference on Machine Learning. PMLR: 1278–1286. arXiv:1401.4082.
Larsen, Anders Boesen Lindbo; Sønderby, Søren Kaae; Larochelle, Hugo; Winther, Ole (2016-06-11). "Autoencoding beyond pixels using a learned similarity metric". International Conference on Machine Learning. PMLR: 1558–1566. arXiv:1512.09300.

neurips.cc (Global: low place; English: low place)

proceedings.neurips.cc

Sohn, Kihyuk; Lee, Honglak; Yan, Xinchen (2015-01-01). Learning Structured Output Representation using Deep Conditional Generative Models (PDF). NeurIPS.

nih.gov (Global: 4^th place; English: 4^th place)

pubmed.ncbi.nlm.nih.gov

Kameoka, Hirokazu; Li, Li; Inoue, Shota; Makino, Shoji (2019-09-01). "Supervised Determined Source Separation with Multichannel Variational Autoencoder". Neural Computation. 31 (9): 1891–1914. doi:10.1162/neco_a_01217. PMID 31335290. S2CID 198168155.
Bengio, Yoshua; Courville, Aaron; Vincent, Pascal (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. Bibcode:2013ITPAM..35.1798B. doi:10.1109/TPAMI.2013.50. ISSN 1939-3539. PMID 23787338. S2CID 393948.
Gao, Rui; Hou, Xingsong; Qin, Jie; Chen, Jiaxin; Liu, Li; Zhu, Fan; Zhang, Zhao; Shao, Ling (2020). "Zero-VAE-GAN: Generating Unseen Features for Generalized and Transductive Zero-Shot Learning". IEEE Transactions on Image Processing. 29: 3665–3680. Bibcode:2020ITIP...29.3665G. doi:10.1109/TIP.2020.2964429. ISSN 1941-0042. PMID 31940538. S2CID 210334032.
Turinici, Gabriel (2021). "Radon-Sobolev Variational Auto-Encoders". Neural Networks. 141: 294–305. arXiv:1911.13135. doi:10.1016/j.neunet.2021.04.018. ISSN 0893-6080. PMID 33933889.

openreview.net (Global: low place; English: low place)

Higgins, Irina; Matthey, Loic; Pal, Arka; Burgess, Christopher; Glorot, Xavier; Botvinick, Matthew; Mohamed, Shakir; Lerchner, Alexander (2016-11-04). beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework. NeurIPS.
Kolouri, Soheil; Pope, Phillip E.; Martin, Charles E.; Rohde, Gustavo K. (2019). "Sliced Wasserstein Auto-Encoders". International Conference on Learning Representations. International Conference on Learning Representations. ICPR.

sciencedirect.com (Global: 149^th place; English: 178^th place)

Turinici, Gabriel (2021). "Radon-Sobolev Variational Auto-Encoders". Neural Networks. 141: 294–305. arXiv:1911.13135. doi:10.1016/j.neunet.2021.04.018. ISSN 0893-6080. PMID 33933889.

semanticscholar.org (Global: 11^th place; English: 8^th place)

api.semanticscholar.org

Pinheiro Cinelli, Lucas; et al. (2021). "Variational Autoencoder". Variational Methods for Machine Learning with Applications to Deep Networks. Springer. pp. 111–149. doi:10.1007/978-3-030-70679-1_5. ISBN 978-3-030-70681-4. S2CID 240802776.
Hsu, Wei-Ning; Zhang, Yu; Glass, James (December 2017). "Unsupervised domain adaptation for robust speech recognition via variational autoencoder-based data augmentation". 2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU). pp. 16–23. arXiv:1707.06265. doi:10.1109/ASRU.2017.8268911. ISBN 978-1-5090-4788-8. S2CID 22681625.
Xu, Weidi; Sun, Haoze; Deng, Chao; Tan, Ying (2017-02-12). "Variational Autoencoder for Semi-Supervised Text Classification". Proceedings of the AAAI Conference on Artificial Intelligence. 31 (1). doi:10.1609/aaai.v31i1.10966. S2CID 2060721.
Kameoka, Hirokazu; Li, Li; Inoue, Shota; Makino, Shoji (2019-09-01). "Supervised Determined Source Separation with Multichannel Variational Autoencoder". Neural Computation. 31 (9): 1891–1914. doi:10.1162/neco_a_01217. PMID 31335290. S2CID 198168155.
Bengio, Yoshua; Courville, Aaron; Vincent, Pascal (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. Bibcode:2013ITPAM..35.1798B. doi:10.1109/TPAMI.2013.50. ISSN 1939-3539. PMID 23787338. S2CID 393948.
Gao, Rui; Hou, Xingsong; Qin, Jie; Chen, Jiaxin; Liu, Li; Zhu, Fan; Zhang, Zhao; Shao, Ling (2020). "Zero-VAE-GAN: Generating Unseen Features for Generalized and Transductive Zero-Shot Learning". IEEE Transactions on Image Processing. 29: 3665–3680. Bibcode:2020ITIP...29.3665G. doi:10.1109/TIP.2020.2964429. ISSN 1941-0042. PMID 31940538. S2CID 210334032.

thecvf.com (Global: low place; English: low place)

openaccess.thecvf.com

Ehsan Abbasnejad, M.; Dick, Anthony; van den Hengel, Anton (2017). Infinite Variational Autoencoder for Semi-Supervised Learning. pp. 5888–5897.

worldcat.org (Global: 5^th place; English: 5^th place)

search.worldcat.org

Bengio, Yoshua; Courville, Aaron; Vincent, Pascal (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. Bibcode:2013ITPAM..35.1798B. doi:10.1109/TPAMI.2013.50. ISSN 1939-3539. PMID 23787338. S2CID 393948.
Gao, Rui; Hou, Xingsong; Qin, Jie; Chen, Jiaxin; Liu, Li; Zhu, Fan; Zhang, Zhao; Shao, Ling (2020). "Zero-VAE-GAN: Generating Unseen Features for Generalized and Transductive Zero-Shot Learning". IEEE Transactions on Image Processing. 29: 3665–3680. Bibcode:2020ITIP...29.3665G. doi:10.1109/TIP.2020.2964429. ISSN 1941-0042. PMID 31940538. S2CID 210334032.
Turinici, Gabriel (2021). "Radon-Sobolev Variational Auto-Encoders". Neural Networks. 141: 294–305. arXiv:1911.13135. doi:10.1016/j.neunet.2021.04.018. ISSN 0893-6080. PMID 33933889.

Variational autoencoder (English Wikipedia)

aaai.org (Global: 9,352nd place; English: 5,696th place)

ojs.aaai.org

arxiv.org (Global: 69th place; English: 59th place)

books.google.com (Global: 3rd place; English: 3rd place)

doi.org (Global: 2nd place; English: 2nd place)

harvard.edu (Global: 18th place; English: 17th place)

ui.adsabs.harvard.edu

lilianweng.github.io (Global: low place; English: low place)

mit.edu (Global: 415th place; English: 327th place)

direct.mit.edu

mlr.press (Global: low place; English: low place)

proceedings.mlr.press

neurips.cc (Global: low place; English: low place)

proceedings.neurips.cc

nih.gov (Global: 4th place; English: 4th place)

pubmed.ncbi.nlm.nih.gov

openreview.net (Global: low place; English: low place)

sciencedirect.com (Global: 149th place; English: 178th place)

semanticscholar.org (Global: 11th place; English: 8th place)

api.semanticscholar.org

thecvf.com (Global: low place; English: low place)

openaccess.thecvf.com

worldcat.org (Global: 5th place; English: 5th place)

search.worldcat.org

aaai.org (Global: 9,352^nd place; English: 5,696^th place)

arxiv.org (Global: 69^th place; English: 59^th place)

books.google.com (Global: 3^rd place; English: 3^rd place)

doi.org (Global: 2^nd place; English: 2^nd place)

harvard.edu (Global: 18^th place; English: 17^th place)

mit.edu (Global: 415^th place; English: 327^th place)

nih.gov (Global: 4^th place; English: 4^th place)

sciencedirect.com (Global: 149^th place; English: 178^th place)

semanticscholar.org (Global: 11^th place; English: 8^th place)

worldcat.org (Global: 5^th place; English: 5^th place)