Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Bidirectional recurrent neural networks
19976.2k citationsMike Schuster, Kuldip K. PaliwalIEEE Transactions on Signal Processingprofile →
Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions
20181.4k citationsJonathan Shen, Ruoming Pang et al.profile →
This map shows the geographic impact of Mike Schuster'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 Mike Schuster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mike Schuster more than expected).
This network shows the impact of papers produced by Mike Schuster. 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 Mike Schuster. The network helps show where Mike Schuster may publish in the future.
Co-authorship network of co-authors of Mike Schuster
This figure shows the co-authorship network connecting the top 25 collaborators of Mike Schuster.
A scholar is included among the top collaborators of Mike Schuster 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 Mike Schuster. Mike Schuster 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
1.
Shen, Jonathan, Ruoming Pang, Ron J. Weiss, et al.. (2018). Natural TTS Synthesis by Conditioning Wavenet on MEL Spectrogram Predictions. 4779–4783.1414 indexed citations breakdown →
2.
Johnson, Melvin, Mike Schuster, Quoc V. Le, et al.. (2017). Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation. Transactions of the Association for Computational Linguistics. 5. 339–351.896 indexed citations breakdown →
Zen, Heiga, Andrew Senior, & Mike Schuster. (2013). Statistical parametric speech synthesis using deep neural networks. 7962–7966.554 indexed citations breakdown →
6.
Schuster, Mike, et al.. (2012). Japanese and Korean voice search. 5149–5152.418 indexed citations breakdown →
7.
Asente, Paul, et al.. (2007). Dynamic planar map illustration. ACM Transactions on Graphics. 26(3). 30–30.24 indexed citations
Lyons, Michael J., et al.. (2002). Comparison between geometry-based and Gabor-wavelets-based facial expression recognition using multi-layer perceptron. 454–459.413 indexed citations breakdown →
Browne, Gina, Jacqueline Roberts, Carolyn Byrne, et al.. (1995). Public health nursing clientele shared with social assistance: proportions, characteristics and policy implications.. PubMed. 86(3). 155–61.2 indexed citations
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.