H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 82 Citations 138,510 179 World Ranking 386 National Ranking 16

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Artificial neural network

His primary scientific interests are in Artificial intelligence, Machine learning, Deep learning, Artificial neural network and Speech recognition. His studies in Generative grammar, Benchmark, Machine translation, Backpropagation and Discriminative model are all subfields of Artificial intelligence research. His research investigates the connection with Backpropagation and areas like Theoretical computer science which intersect with concerns in Image translation.

Aaron Courville has researched Discriminative model in several fields, including Approximate inference and Resolution. His Machine learning study frequently draws connections to adjacent fields such as Training set. His Deep learning study incorporates themes from Layer, Probabilistic logic, Feature learning, Software and Computation.

His most cited work include:

  • Generative Adversarial Nets (19444 citations)
  • Deep Learning (7910 citations)
  • Representation Learning: A Review and New Perspectives (6277 citations)

What are the main themes of his work throughout his whole career to date?

His scientific interests lie mostly in Artificial intelligence, Machine learning, Deep learning, Algorithm and Artificial neural network. His Artificial intelligence research includes elements of Natural language processing and Pattern recognition. His research in Pattern recognition intersects with topics in Image resolution and Structured prediction.

Aaron Courville focuses mostly in the field of Machine learning, narrowing it down to topics relating to Training set and, in certain cases, Robustness. The concepts of his Deep learning study are interwoven with issues in Visual reasoning, Benchmark and Variation. His Recurrent neural network research focuses on Convolutional neural network and how it connects with Speech recognition.

He most often published in these fields:

  • Artificial intelligence (68.26%)
  • Machine learning (30.03%)
  • Deep learning (13.65%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (68.26%)
  • Generalization (7.85%)
  • Natural language processing (10.24%)

In recent papers he was focusing on the following fields of study:

Aaron Courville mostly deals with Artificial intelligence, Generalization, Natural language processing, Reinforcement learning and Language model. His Artificial intelligence research incorporates elements of Machine learning and Pattern recognition. Aaron Courville works mostly in the field of Machine learning, limiting it down to topics relating to State and, in certain cases, Moving average, as a part of the same area of interest.

His work in Natural language processing tackles topics such as Semantics which are related to areas like Categorical semantics and Domain. His Reinforcement learning research incorporates themes from Multimedia, Intelligent tutoring system, Interface and Data science. Aaron Courville has included themes like Text corpus, Parsing and Word error rate in his Language model study.

Between 2019 and 2021, his most popular works were:

  • Generative adversarial networks (78 citations)
  • Out-of-Distribution Generalization via Risk Extrapolation (REx) (59 citations)
  • Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models. (19 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Programming language

His primary areas of investigation include Artificial intelligence, Robustness, Machine learning, Ode and Flow. The Artificial intelligence study which covers Pattern recognition that intersects with Invariant. His Robustness research includes themes of Robust optimization, Entropy and Covariate shift.

His research investigates the connection between Machine learning and topics such as State that intersect with issues in Reinforcement learning. His Ode study combines topics in areas such as Latent variable and Hamiltonian. His Artificial neural network research is multidisciplinary, relying on both Regularization and Training set.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Generative Adversarial Nets

Ian Goodfellow;Jean Pouget-Abadie;Mehdi Mirza;Bing Xu.
neural information processing systems (2014)

22768 Citations

Deep Learning

Ian Goodfellow;Yoshua Bengio;Aaron Courville.
(2016)

20521 Citations

Representation Learning: A Review and New Perspectives

Y. Bengio;A. Courville;P. Vincent.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2013)

7322 Citations

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

Kelvin Xu;Jimmy Ba;Ryan Kiros;Kyunghyun Cho.
international conference on machine learning (2015)

5793 Citations

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

Kelvin Xu;Jimmy Ba;Ryan Kiros;Kyunghyun Cho.
arXiv: Learning (2015)

4026 Citations

Improved training of wasserstein GANs

Ishaan Gulrajani;Faruk Ahmed;Martin Arjovsky;Vincent Dumoulin.
neural information processing systems (2017)

3153 Citations

Generative Adversarial Networks

Ian Goodfellow;Jean Pouget-Abadie;Mehdi Mirza;Bing Xu.
arXiv: Machine Learning (2014)

2473 Citations

Why Does Unsupervised Pre-training Help Deep Learning?

Dumitru Erhan;Aaron C. Courville;Yoshua Bengio;Pascal Vincent.
international conference on artificial intelligence and statistics (2010)

2327 Citations

Why Does Unsupervised Pre-training Help Deep Learning?

Dumitru Erhan;Yoshua Bengio;Aaron Courville;Pierre-Antoine Manzagol.
Journal of Machine Learning Research (2010)

2240 Citations

Maxout Networks

Ian Goodfellow;David Warde-Farley;Mehdi Mirza;Aaron Courville.
(2013)

2172 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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