Who Cited It

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

2015 · arXiv (Cornell University) · 24,404 citations · 32 from inside this corpus

Sergey Ioffe, Christian Szegedy

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh… (2015)Batch Normalization: Accelera…Dropout: a simple way to prevent neural networks from overfitting (2014)Dropout: a simple way to prev…Understanding the difficulty of training deep feedforward neural networks (2010)Understanding the difficulty …Adaptive Subgradient Methods for Online Learning and Stochastic Optimization (2010)Adaptive Subgradient Methods …On the difficulty of training Recurrent Neural Networks (2012)On the difficulty of training…On the importance of initialization and momentum in deep learning (2013)On the importance of initiali…Xception: Deep Learning with Depthwise Separable Convolutions (2017)Xception: Deep Learning with …Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning (2017)Inception-v4, Inception-ResNe…Momentum Contrast for Unsupervised Visual Representation Learning (2020)Momentum Contrast for Unsuper…Aggregated Residual Transformations for Deep Neural Networks (2017)Aggregated Residual Transform…Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks (2017)Model-Agnostic Meta-Learning …[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)][No title in the source recor…Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning (2017)Inception-v4, Inception-ResNe…Bootstrap your own latent: A new approach to self-supervised Learning (2020)Bootstrap your own latent: A …Exploring Simple Siamese Representation Learning (2021)Exploring Simple Siamese Repr…Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised … (2018)Virtual Adversarial Training:…Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions (2018)Natural TTS Synthesis by Cond…Unsupervised Visual Representation Learning by Context Prediction (2015)Unsupervised Visual Represent…Convolutional 2D Knowledge Graph Embeddings (2018)Convolutional 2D Knowledge Gr…MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmenta… (2019)MultiResUNet : Rethinking the…Barren plateaus in quantum neural network training landscapes (2018)Barren plateaus in quantum ne…Deep visual domain adaptation: A survey (2018)Deep visual domain adaptation…Deep Speech 2: End-to-End Speech Recognition in English and Mandarin (2015)Deep Speech 2: End-to-End Spe…DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep… (2018)DeepSurv: personalized treatm…Return of Frustratingly Easy Domain Adaptation (2016)Return of Frustratingly Easy …Generative adversarial network in medical imaging: A review (2019)Generative adversarial networ…Review of Deep Learning Algorithms and Architectures (2019)Review of Deep Learning Algor…Tacotron: Towards End-to-End Speech Synthesis (2017)Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervise… (2019)A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer … (2017)Over-the-Air Deep Learning Based Radio Signal Classification (2018)Over-the-Air Deep Learning Ba…ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders (2023)ConvNeXt V2: Co-designing and…ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speak… (2020)ECAPA-TDNN: Emphasized Channe…[No title in the source record — Newcastle University ePrints (Newcastle Univesity)]Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates (2017)Deep reinforcement learning f…Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach (2017)Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activa… (2016)Quantized Neural Networks: Tr…
36 of 37 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.
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What this paper cites, inside the corpus

PaperYearCited
Dropout: a simple way to prevent neural networks from overfitting201434,236
Understanding the difficulty of training deep feedforward neural networks201012,673
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization20108,621
On the difficulty of training Recurrent Neural Networks20123,801
On the importance of initialization and momentum in deep learning20133,523

What cites it, inside the corpus

PaperYearCited
Xception: Deep Learning with Depthwise Separable Convolutions201719,457
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning201712,734
Momentum Contrast for Unsupervised Visual Representation Learning202012,515
Aggregated Residual Transformations for Deep Neural Networks201712,015
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks20175,794
[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]4,858
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning20174,487
Bootstrap your own latent: A new approach to self-supervised Learning20203,447
Exploring Simple Siamese Representation Learning20213,438
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised …20182,873
Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions20182,708
Unsupervised Visual Representation Learning by Context Prediction20152,699
Convolutional 2D Knowledge Graph Embeddings20182,467
MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmenta…20192,334
Barren plateaus in quantum neural network training landscapes20182,289
Deep visual domain adaptation: A survey20182,232
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin20152,181
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep…20182,013
Return of Frustratingly Easy Domain Adaptation20161,910
Generative adversarial network in medical imaging: A review20191,902
Review of Deep Learning Algorithms and Architectures20191,878
Tacotron: Towards End-to-End Speech Synthesis20171,749
Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervise…20191,730
A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer …20171,660
Over-the-Air Deep Learning Based Radio Signal Classification20181,604
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders20231,523
ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speak…20201,496
[No title in the source record — Newcastle University ePrints (Newcastle Univesity)]1,494
Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates20171,468
Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach20171,464
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activa…20161,420

Links

DOI · Open access copy · OpenAlex record

Topics

Neural Networks and ApplicationsComputer Science
Domain Adaptation and Few-Shot LearningComputer Science
Machine Learning and ELMComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports2 author record(s) attached.
  • supports23 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:40+00:00.

sha256 7e3d99a592f7f61f…