Ivo Danihelka

9.6k total citations · 2 hit papers
9 papers, 1.5k citations indexed

About

Ivo Danihelka is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Ivo Danihelka has authored 9 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Ivo Danihelka's work include Generative Adversarial Networks and Image Synthesis (4 papers), Neural Networks and Applications (3 papers) and Advanced Memory and Neural Computing (3 papers). Ivo Danihelka is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (4 papers), Neural Networks and Applications (3 papers) and Advanced Memory and Neural Computing (3 papers). Ivo Danihelka collaborates with scholars based in United Kingdom and United States. Ivo Danihelka's co-authors include Alex Graves, Karol Gregor, Daan Wierstra, Danilo Jimenez Rezende, Greg Wayne, Nal Kalchbrenner, Tim Harley, Phil Blunsom, Demis Hassabis and Sergio Gómez Colmenarejo and has published in prestigious journals such as Nature, arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Ivo Danihelka

9 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

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.

Hybrid computing using a neural network with dynamic external memory

2016 683 citations Alex Graves, Greg Wayne et al. Nature profile →
DRAW: A Recurrent Neural Network For Image Generation

2015 478 citations Karol Gregor, Ivo Danihelka et al. International Conference on Machine Learning profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ivo Danihelka United Kingdom	9	855	638	212	118	112	9	1.5k
Derek Rose United States	12	635 0.7×	442 0.7×	161 0.8×	88 0.7×	133 1.2×	29	1.6k
Çaǧlar Gülçehre Canada	11	1.0k 1.2×	526 0.8×	142 0.7×	84 0.7×	188 1.7×	26	1.7k
Rodolfo Zunino Italy	23	883 1.0×	786 1.2×	242 1.1×	173 1.5×	141 1.3×	167	1.9k
Tao Xiong United States	16	572 0.7×	493 0.8×	222 1.0×	192 1.6×	181 1.6×	40	1.5k
Jie Song China	23	621 0.7×	910 1.4×	177 0.8×	147 1.2×	79 0.7×	103	2.0k
Jose L. Part United Kingdom	5	1.2k 1.3×	542 0.8×	174 0.8×	122 1.0×	74 0.7×	12	1.7k
Humberto Sossa Mexico	24	712 0.8×	795 1.2×	237 1.1×	201 1.7×	117 1.0×	190	2.0k
Alexander Lerchner United States	8	711 0.8×	616 1.0×	66 0.3×	160 1.4×	144 1.3×	15	1.4k
Phil Blunsom United Kingdom	14	966 1.1×	235 0.4×	345 1.6×	89 0.8×	81 0.7×	29	1.4k
Min Lin China	15	831 1.0×	991 1.6×	91 0.4×	55 0.5×	73 0.7×	40	1.9k

Countries citing papers authored by Ivo Danihelka

Since Specialization

Citations

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

Fields of papers citing papers by Ivo Danihelka

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivo Danihelka

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Gregor, Karol, Frederic Besse, Danilo Jimenez Rezende, Ivo Danihelka, & Daan Wierstra. (2016). Towards Conceptual Compression. Neural Information Processing Systems. 29. 3549–3557. 45 indexed citations

2.

Kalchbrenner, Nal, Ivo Danihelka, & Alex Graves. (2016). Grid Long Short-Term Memory. arXiv (Cornell University). 106 indexed citations

3.

Graves, Alex, Greg Wayne, Malcolm Reynolds, et al.. (2016). Hybrid computing using a neural network with dynamic external memory. Nature. 538(7626). 471–476. 683 indexed citations breakdown →

4.

Danihelka, Ivo, Greg Wayne, Benigno Uría, Nal Kalchbrenner, & Alex Graves. (2016). Associative Long Short-Term Memory. arXiv (Cornell University). 1986–1994. 52 indexed citations

5.

Rezende, Danilo Jimenez, Shakir Mohamed, Ivo Danihelka, Karol Gregor, & Daan Wierstra. (2016). One-Shot Generalization in Deep Generative Models. arXiv (Cornell University). 1521–1529. 32 indexed citations

6.

Rae, Jack W., Jonathan J. Hunt, Tim Harley, et al.. (2016). Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes. arXiv (Cornell University). 29. 3628–3636. 25 indexed citations

7.

Gregor, Karol, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, & Daan Wierstra. (2015). DRAW: A Recurrent Neural Network For Image Generation. International Conference on Machine Learning. 1462–1471. 478 indexed citations breakdown →

8.

Graves, Alex, Greg Wayne, & Ivo Danihelka. (2014). Neural Turing Machines. arXiv (Cornell University). 54 indexed citations

9.

Gregor, Karol, Ivo Danihelka, Andriy Mnih, Charles Blundell, & Daan Wierstra. (2013). Deep AutoRegressive Networks. arXiv (Cornell University). 1242–1250. 54 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.

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