Who Cited It

Learning Deep Architectures for AI

2009 · Foundations and Trends® in Machine Learning · 6,951 citations · 25 from inside this corpus

Yoshua Bengio

No abstract in the source record.

Learning Deep Architectures for AI (2009)Learning Deep Architectures f…Deep learning in neural networks: An overview (2014)Deep learning in neural netwo…Machine learning: Trends, perspectives, and prospects (2015)Machine learning: Trends, per…A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures (2019)A Review of Recurrent Neural …Curriculum learning (2009)Curriculum learningA random forest guided tour (2016)A random forest guided tourThe Limitations of Deep Learning in Adversarial Settings (2016)The Limitations of Deep Learn…Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review (2017)Deep Convolutional Neural Net…Machine Learning in Medicine (2015)Machine Learning in MedicineA few useful things to know about machine learning (2012)A few useful things to know a…A survey of deep neural network architectures and their applications (2016)A survey of deep neural netwo…Deep learning for healthcare: review, opportunities and challenges (2017)Deep learning for healthcare:…Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition (2011)Context-Dependent Pre-Trained…State-of-the-art in artificial neural network applications: A survey (2018)State-of-the-art in artificia…Structural Deep Network Embedding (2016)Structural Deep Network Embed…Privacy-Preserving Deep Learning (2015)Privacy-Preserving Deep Learn…Deep visual domain adaptation: A survey (2018)Deep visual domain adaptation…Learning deep structured semantic models for web search using clickthrough data (2013)Learning deep structured sema…Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey (2018)Threat of Adversarial Attacks…Practical Recommendations for Gradient-Based Training of Deep Architectures (2012)Practical Recommendations for…Causability and explainability of artificial intelligence in medicine (2019)Causability and explainabilit…Trends in extreme learning machines: A review (2014)Trends in extreme learning ma…A State-of-the-Art Survey on Deep Learning Theory and Architectures (2019)A State-of-the-Art Survey on …A survey on deep learning and its applications (2021)A survey on deep learning and…Extreme Learning Machine for Multilayer Perceptron (2015)Extreme Learning Machine for …Explaining nonlinear classification decisions with deep Taylor decomposition (2016)Explaining nonlinear classifi…
25 of 25 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What cites it, inside the corpus

PaperYearCited
Deep learning in neural networks: An overview201418,236
Machine learning: Trends, perspectives, and prospects20159,947
A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures20195,628
Curriculum learning20095,154
A random forest guided tour20164,026
The Limitations of Deep Learning in Adversarial Settings20163,980
Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review20173,570
Machine Learning in Medicine20153,534
A few useful things to know about machine learning20123,338
A survey of deep neural network architectures and their applications20163,285
Deep learning for healthcare: review, opportunities and challenges20173,115
Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition20113,089
State-of-the-art in artificial neural network applications: A survey20183,071
Structural Deep Network Embedding20162,843
Privacy-Preserving Deep Learning20152,325
Deep visual domain adaptation: A survey20182,232
Learning deep structured semantic models for web search using clickthrough data20132,099
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey20182,090
Practical Recommendations for Gradient-Based Training of Deep Architectures20121,960
Causability and explainability of artificial intelligence in medicine20191,851
Trends in extreme learning machines: A review20141,752
A State-of-the-Art Survey on Deep Learning Theory and Architectures20191,619
A survey on deep learning and its applications20211,548
Extreme Learning Machine for Multilayer Perceptron20151,475
Explaining nonlinear classification decisions with deep Taylor decomposition20161,413

Links

DOI · OpenAlex record

Topics

Anomaly Detection Techniques and ApplicationsComputer Science

Is this record sound?

partial

One field of this record is missing or disagrees with another. What is shown below is what the source publishes.

  • supports1 author record(s) attached.
  • weakensNo references are recorded despite 6,951 citations. A paper this heavily cited did not cite nothing, so the record is incomplete.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:43+00:00.

sha256 5cad55ac5d4d41e1…