The DOI matches its Crossref record; 29 of the 32 references it cites were found in a registry or an index.
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“Ladder autoencoders make use of lateral connections and local noise injection to introduce an unsupervised cost function, based on internal reconstructions, that can be readily combined with supervised cost functions defined on the networks top layer outputs (Valpola, 2015).”
From Toward an integration of deep learning and neuroscience (2016) · cites this paper as Valpola, 2015
Citations
Cites
ImageNet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Reducing the dimensionality of data with neural networks
Hinton, G. E., & Salakhutdinov, R. R. (2006) · Science · doi:10.1126/science.1127647 · Cited by 20,928
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570
A fast learning algorithm for deep belief nets
Hinton, G. E., Osindero, S., & Teh, Y.-W. (2006) · Neural Computation · doi:10.1162/neco.2006.18.7.1527 · Cited by 16,336
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Extracting and composing robust features with denoising autoencoders
Vincent, P., Larochelle, H., Bengio, Y., & Manzagol, P.-A. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08 · doi:10.1145/1390156.1390294 · Cited by 7,436
Fukushima, K. (1980) · Biological Cybernetics · doi:10.1007/bf00344251 · Cited by 5,759
A Fast Fixed-Point Algorithm for Independent Component Analysis
Hyvärinen, A., & Erkki Oja, A. (1997) · Neural Computation · doi:10.1162/neco.1997.9.7.1483 · Cited by 3,373
Jordan, M. I. (1998) · Springer eBooks · doi:10.1007/978-94-011-5014-9 · Cited by 2,449
Cited by
Sorted by citations
Deep Learning for IoT Big Data and Streaming Analytics: A Survey
Mohammadi, M., Al-Fuqaha, A., Sorour, S., & Guizani, M. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2844341 · Cited by 1,471
Semi-Supervised Learning with Ladder NetworksPreprint
Rasmus, A., Harri Valpola, B., Honkala, M., Berglund, M., & Raiko, T. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1507.02672 · Cited by 941
Deep Predictive Coding Networks for Video Prediction and Unsupervised LearningPreprint
Lotter, W. E., Kreiman, G., & Cox, D. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.08104 · Cited by 904
Semi Supervised Semantic Segmentation Using Generative Adversarial Network
Souly, N., Spampinato, C., & Shah, M. A. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.606 · Cited by 597
Classification-Reconstruction Learning for Open-Set Recognition
Yoshihashi, R., Shao, W. Q., Kawakami, R., You, S., Iida, M., & Naemura, T. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00414 · Cited by 509
Metadata
- Authors
- Valpola, H.
- Venue
- Advances in Independent Component Analysis and Learning Machines
- Publisher
- Elsevier
- Published
- 2015
- Pages
- 143-171
- OpenAlex
- W2147062276
- Cited by
- 181
- References
- 32
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 9 · 2023: 7 · 2022: 12 · 2021: 26 · 2020: 30 · 2019: 22 · 2018: 29 · 2017: 20 · 2016: 15 · 2015: 4
- FWCI
- 45.15
- Type
- book chapter
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Elsevier eBooks (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Physical Sciences › Computer Science › Signal Processing › Blind Source Separation Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Keywords
- unsupervised deep learning, autoencoder, hierarchical latent variable models, denoising autoencoder, source separation, invariant feature learning
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