Barret Zoph

28.1k citations
20 papers · 4.9k indexed · 5 hit papers · h-index 12
Topics
Advanced Neural Network Applications (8 papers)Natural Language Processing Techniques (5 papers)Domain Adaptation and Few-Shot Learning (5 papers)
Journals
2021 IEEE/CVF International Conference on Computer Vision (ICCV)arXiv (Cornell University)Neural Information Processing Systems
Partner nations
United StatesGermany

In The Last Decade

Barret Zoph

19 papers receiving 4.7k citations

Hit Papers

SpecAugment: A Simple Data Augmentation Method for Automa...20162026201920222019201920182016201850010001.5k2.0k

Peers

Barret Zoph
Comparison fields: 5 of 154
  • Artificial Intelligence 3.3k
  • Computer Vision and Pattern Recognition 2.0k
  • Signal Processing 1.5k
  • Electrical and Electronic Engineering 224
  • Radiology, Nuclear Medicine and Imaging 197
Replace Bhiksha Raj with:
Bhiksha Raj United States
Hui Jiang Canada
Ossama Abdel‐Hamid Canada
Bhuvana Ramabhadran United States
Wenwu Wang United Kingdom
Haşim Sak United States
Chuang Gan United States
Yuexian Zou China
Anderson Rocha Brazil
Kihyuk Sohn United States
Barret Zoph relative to Bhiksha Raj United States Bhiksha Raj's profile →
Citations per field
00.5×2.6×
Bhiksha Raj · 1×
Citations per year

Countries citing papers authored by Barret Zoph

Since Specialization
Citations

This map shows the geographic impact of Barret Zoph's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Barret Zoph with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Barret Zoph more than expected).

Fields of papers citing papers by Barret Zoph

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Barret Zoph. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Barret Zoph. The network helps show where Barret Zoph may publish in the future.

Co-authorship network of co-authors of Barret Zoph

This figure shows the co-authorship network connecting the top 25 collaborators of Barret Zoph. A scholar is included among the top collaborators of Barret Zoph based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Barret Zoph. Barret Zoph is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 11
2 25
3 26
4
Revisiting ResNets: Improved Training and Scaling Strategies
2
5 40
6
Revisiting ResNets: Improved Training Methodologies and Scaling Principles
1
7
Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation.
2
8
Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation
5
9
Rethinking Pre-training and Self-training
21
10
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
61
11
AutoAugment: Learning Augmentation Strategies From Databreakdown →
1464
12
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognitionbreakdown →
2055
13
Faster Discovery of Neural Architectures by Searching for Paths in a Large Model
6
14
Understanding and Simplifying One-Shot Architecture Searchbreakdown →
234
15
Efficient Neural Architecture Search via Parameters Sharingbreakdown →
598
16
EXPLORING NEURAL ARCHITECTURE SEARCH FOR LANGUAGE TASKS
0
17
Neural optimizer search with reinforcement learning
37
18
Neural Architecture Search with Reinforcement Learningbreakdown →
336
19 18
20 3

About Barret Zoph

Barret Zoph is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 20 papers that have together received 4.9k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Natural Language Processing Techniques (5 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Signal Processing (1.5k citations), Artificial Intelligence (3.3k citations) and Computer Vision and Pattern Recognition (2.0k citations). Barret Zoph has collaborated with scholars based in United States and Germany. Frequent co-authors include Quoc V. Le, Ekin D. Cubuk, Vijay Vasudevan, Yu Zhang, Daniel Park, Chung‐Cheng Chiu, William Chan, Jeff Dean, Hieu Pham and Melody Y. Guan. Their work appears in journals such as 2021 IEEE/CVF International Conference on Computer Vision (ICCV), arXiv (Cornell University) and Neural Information Processing Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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