Anssi Kanervisto

9 papers receiving 846 citations

Hit Papers

Stable-Baselines3: Reliable Reinforcement Learning Implem...20212026202220242021200400600

Peers

Anssi Kanervisto
Comparison fields: 5 of 99
  • Artificial Intelligence 349
  • Control and Systems Engineering 218
  • Computer Vision and Pattern Recognition 190
  • Electrical and Electronic Engineering 162
  • Automotive Engineering 112
Replace Ashley Hill with:
Ashley Hill France
Antonin Raffin Germany
Gabriel Dulac-Arnold United Kingdom
Maximilian Ernestus Germany
Adam Gleave United Kingdom
Sven Gowal United Kingdom
Mohammad Gheshlaghi Azar United Kingdom
Martijn van Otterlo Netherlands
I. Grondman Netherlands
Bogdan Trăsnea Romania
Anssi Kanervisto relative to Ashley Hill France Ashley Hill's profile →
Citations per field
00.5×3.8×
Ashley Hill · 1×
Citations per year

Countries citing papers authored by Anssi Kanervisto

Since Specialization
Citations

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

Fields of papers citing papers by Anssi Kanervisto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anssi Kanervisto

This figure shows the co-authorship network connecting the top 25 collaborators of Anssi Kanervisto. A scholar is included among the top collaborators of Anssi Kanervisto 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 Anssi Kanervisto. Anssi Kanervisto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 8
2
Stable-Baselines3: Reliable Reinforcement Learning Implementationsbreakdown →
739
3 8
4 51
5 5
6 2
7 7
8
Image-to-Markup Generation with Coarse-to-Fine Attention
42
9 7

About Anssi Kanervisto

Anssi Kanervisto is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 9 papers that have together received 869 indexed citations. Recurring topics across this work include Speech and Audio Processing (3 papers), Music and Audio Processing (3 papers) and Speech Recognition and Synthesis (3 papers). The work is most often cited by research in Artificial Intelligence (349 citations), Control and Systems Engineering (218 citations) and Automotive Engineering (112 citations). Anssi Kanervisto has collaborated with scholars based in Finland, Japan and United States. Frequent co-authors include Antonin Raffin, Ashley Hill, Adam Gleave, Maximilian Ernestus, Ville Hautamäki, Jun Miura, Yuntian Deng, Jeffrey Ling, Alexander M. Rush and Tomi Kinnunen. Their work appears in journals such as Journal of Machine Learning Research, IEEE/ACM Transactions on Audio Speech and Language Processing and IEEE Transactions on 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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