Gabriel Synnaeve

54 papers receiving 1.9k citations

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ResMLP: Feedforward Networks for Image Classification Wit...2020202620222024202220212020100200300400

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Gabriel Synnaeve
Comparison fields: 5 of 114
  • Artificial Intelligence 1.5k
  • Computer Vision and Pattern Recognition 708
  • Signal Processing 546
  • Sociology and Political Science 108
  • Experimental and Cognitive Psychology 76
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Juhan Nam South Korea
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Anmol Gulati United States
Weiran Wang United States
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Countries citing papers authored by Gabriel Synnaeve

Since Specialization
Citations

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

Fields of papers citing papers by Gabriel Synnaeve

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gabriel Synnaeve

This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Synnaeve. A scholar is included among the top collaborators of Gabriel Synnaeve 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 Gabriel Synnaeve. Gabriel Synnaeve 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 4
2 3
3 3
4 1
5
ResMLP: Feedforward Networks for Image Classification With Data-Efficient Trainingbreakdown →
444
6 2
7 61
8 171
9 63
10
A fully differentiable beam search decoder
4
11
Intrinsic motivation and automatic curricula via asymmetric self-play
27
12
Value Propagation Networks.
6
13 6
14
Episodic Exploration for Deep Deterministic Policies for StarCraft Micromanagement
5
15
Quantitative methods for comparing featural representations.
5
16
Weakly Supervised Multi-Embeddings Learning of Acoustic Models.
1
17
Unsupervised Word Segmentation in Context
4
18 1
19 8
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A Dataset for StarCraft AI & an Example of Armies Clustering
22

About Gabriel Synnaeve

Gabriel Synnaeve is a scholar working on Signal Processing, Artificial Intelligence and Software, having authored 54 papers that have together received 2.1k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (24 papers), Artificial Intelligence in Games (15 papers) and Music and Audio Processing (15 papers). The work is most often cited by research in Signal Processing (546 citations), Artificial Intelligence (1.5k citations) and Computer Vision and Pattern Recognition (708 citations). Gabriel Synnaeve has collaborated with scholars based in France, Israel and United States. Frequent co-authors include Ronan Collobert, Emmanuel Dupoux, Nicolas Carion, Pierre Bessìère, Qiantong Xu, Ishan Misra, Aishwarya Kamath, Yann LeCun, Mannat Singh and Vineel Pratap. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, The Journal of the Acoustical Society of America and IEEE Transactions on Computational Intelligence and AI in Games.

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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