Concepedia

Probabilistic Deep Learning

Probabilistic Deep Learning is a subfield of deep learning that integrates probabilistic modeling principles with deep neural architectures to quantify uncertainty, model complex data distributions, and enable principled inference through the explicit use of probability distributions over latent variables and parameters.

978

Publications

86.5K

Citations

3.2K

Authors

1K

Institutions

Publications per year

2017–2026

828

Parents

Publications

978

A survey of deep neural network architectures and their applications

Weibo Liu, Zidong Wang, Xiaohui Liu et al. · Neurocomputing · 2016 · 3.3K citations

, , +12

Stochastic Backpropagation and Approximate Inference in Deep Generative Models

Danilo Jimenez Rezende, Shakir Mohamed, Daan Wierstra · arXiv (Cornell University) · 2014 · 2.7K citations · Full text

, , +15

What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

Alex Kendall, Yarin Gal · arXiv (Cornell University) · 2017 · 2.5K citations · Full text

, , +16

Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations

Honglak Lee, Roger Grosse, Rajesh Ranganath et al. · 2009 · 2.4K citations

, , +15

Conditional Random Fields as Recurrent Neural Networks

Shuai Zheng, Sadeep Jayasumana, Bernardino Romera‐Paredes et al. · 2015 · 2.4K citations · Full text

, , +10

1–5 of 978

Authors

3.2K

  1. YG
    Yarin Gal

    University of Oxford, United Kingdom

    12 publications · 3.5K citations

    12

    h-index

  2. KK
    Kristian Kersting

    Technische Universität Darmstadt, Germany

    10 publications · 296 citations

    10

    h-index

  3. YB
    Yoshua Bengio

    Université de Montréal, Canada

    10 publications · 1.7K citations

    10

    h-index

  4. RP
    Robert Peharz

    Graz University of Technology, Austria

    8 publications · 192 citations

    8

    h-index

  5. AV
    Antonio Vergari

    University of California, Los Angeles, United States

    8 publications · 247 citations

    8

    h-index

1–5 of 3.2K

Institutions

1K

  1. University of Oxford

    Oxford, United Kingdom

    22 h-index

    69 publications

    15.7K citations

  2. Google (United States)

    Mountain View, United States

    19 h-index

    70 publications

    18.3K citations

  3. University of Cambridge

    Cambridge, United Kingdom

    19 h-index

    50 publications

    11.9K citations

  4. University of Toronto

    Toronto, Canada

    19 h-index

    46 publications

    4K citations

  5. Stanford University

    Stanford, United States

    16 h-index

    37 publications

    17.7K citations

  6. Tsinghua University

    Beijing, China

    13 h-index

    53 publications

    2.3K citations

  7. Massachusetts Institute of Technology

    Cambridge, United States

    13 h-index

    29 publications

    1.8K citations

  8. Chinese Academy of Sciences

    Beijing, China

    11 h-index

    21 publications

    2.2K citations

1–8 of 1K

Venues

  1. arXiv (Cornell University)

    Repository · 227 publications · 24.5K citations

    62

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 29 publications · 1.5K citations

    20

    h-index

  3. Neural Information Processing Systems

    Conference · 14 publications · 1.7K citations

    13

    h-index

  4. Reliability Engineering & System Safety

    12 publications · 924 citations

    12

    h-index

  5. Neurocomputing

    12 publications · 4.1K citations

    12

    h-index

1–5