Sam Gross

32.5k citations
6 papers · 8.0k · 3 hit papers · h-index 5

Impact in

    • Advanced Neural Network Applications
    • Multimodal Machine Learning Applications
    • Advanced Image and Video Retrieval Techniques
    • Advanced Vision and Imaging
    • Topic Modeling
    • Natural Language Processing Techniques
    • Domain Adaptation and Few-Shot Learning
    • Speech Recognition and Synthesis

Papers in

Sam Gross

6 papers receiving 7.6k citations

Sam Gross's Hit Papers

fairseq: A Fast, Extensible Toolkit for Sequence Modeling 2019 · 1.4k citations
1.4k0+3+6Years since publication10002.0k3.0k4.0k5.0k

Peers

Sam Gross
Comparison fields: 5 of 196
  • Computer Vision and Pattern Recognition 3.4k
  • Artificial Intelligence 3.8k
  • Signal Processing 585
  • Media Technology 402
  • Computational Mathematics 25
Replace Zeming Lin with:
Zeming Lin China
Adam Paszke United States
Edward Z. Yang United States
Adam Lerer United States
Alban Desmaison United Kingdom
Zachary DeVito United States
Soumith Chintala United States
Joachim M. Buhmann Switzerland
Xavier Glorot Canada
Yang Song Australia
Sam Gross relative to Zeming Lin China Zeming Lin's profile →
Citations per field
00.5×1.5×
Zeming Lin · 1×
Citations per year

Countries citing papers authored by Sam Gross

Since Specialization
Citations

This map shows the geographic impact of Sam Gross'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 Sam Gross with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sam Gross more than expected).

Fields of papers citing papers by Sam Gross

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sam Gross. 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 Sam Gross. The network helps show where Sam Gross may publish in the future.

Co-authors

The 25 scholars most cited alongside Sam Gross, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sam Gross Line = papers co-authored together Sam Gross links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1
Automatic differentiation in PyTorch
Hit paper breakdown →
20175752
2
fairseq: A Fast, Extensible Toolkit for Sequence Modeling
Hit paper breakdown →
20191410
3
A universal SNP and small-indel variant caller using deep neural networks
Hit paper breakdown →
2018824
4 201736
5 201623
6
Energy-Based Models for Text
20202

About Sam Gross

Sam Gross is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Statistical and Nonlinear Physics and Signal Processing, having authored 6 papers that have together received 8.0k indexed citations. Recurring topics across this work include Topic Modeling (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Genomics and Rare Diseases (1 paper), Computational and Text Analysis Methods (1 paper), RNA and protein synthesis mechanisms (1 paper), Advanced Vision and Imaging (1 paper), Music and Audio Processing (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (3.4k citations), Artificial Intelligence (3.8k citations), Signal Processing (585 citations), Media Technology (402 citations) and Computational Mathematics (25 citations). Sam Gross has collaborated with scholars based in Israel and United States. Frequent co-authors include Adam Lerer, Zachary DeVito, Alban Desmaison, Adam Paszke, Zeming Lin, Soumith Chintala, Edward Z. Yang, Luca Antiga, Myle Ott and Michael Auli. Their work appears in journals such as Nature Biotechnology and arXiv (Cornell University).

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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