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.
Recurrent neural network based language model
20103.3k citationsTomáš Mikolov, Martin Karafiát et al.profile →
Extensions of recurrent neural network language model
2011929 citationsTomáš Mikolov, Lukáš Burget et al.profile →
Sequence-discriminative training of deep neural networks
2013458 citationsKarel Veselý, Arnab Ghoshal et al.Edinburgh Research Explorerprofile →
Strategies for training large scale neural network language models
2011329 citationsTomáš Mikolov, Anoop Deoras et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Lukáš Burget'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 Lukáš Burget with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lukáš Burget more than expected).
This network shows the impact of papers produced by Lukáš Burget. 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 Lukáš Burget. The network helps show where Lukáš Burget may publish in the future.
Co-authorship network of co-authors of Lukáš Burget
This figure shows the co-authorship network connecting the top 25 collaborators of Lukáš Burget.
A scholar is included among the top collaborators of Lukáš Burget 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 Lukáš Burget. Lukáš Burget is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Szöke, Igor, et al.. (2014). BUT QUESST 2014 System Description. MediaEval.10 indexed citations
11.
Szöke, Igor, et al.. (2013). BUT SWS 2013 - Massive Parallel Approach. MediaEval.7 indexed citations
12.
Veselý, Karel, Arnab Ghoshal, Lukáš Burget, & Daniel Povey. (2013). Sequence-discriminative training of deep neural networks. Edinburgh Research Explorer. 2345–2349.458 indexed citations breakdown →
13.
Ferrer, Luciana, Lukáš Burget, Oldřich Plchot, & Nicolas Scheffer. (2012). A unified approach for audio characterization and its application to speaker recognition.. 317–323.17 indexed citations
14.
Streuli, R, et al.. (2012). Spontaneous splenic rupture following plasmapheresis in a patient with refractory amiodarone-induced thyrotoxicosis. 15th International & 14th European Congress of Endocrinology. 29.1 indexed citations
15.
Mikolov, Tomáš, Anoop Deoras, Daniel Povey, Lukáš Burget, & Jaň Černocký. (2011). Strategies for training large scale neural network language models. 196–201.329 indexed citations breakdown →
Plchot, Oldřich, Niko Brümmer, Lukáš Burget, et al.. (2010). Data selection and calibration issues in automatic language recognition - investigation with BUT-AGNITIO NIST LRE 2009 system.. 37.21 indexed citations
Jain, Prachi, et al.. (2002). Distributed Speech Recognition. SHILAP Revista de lepidopterología.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.