Klaus Greff

11.1k citations
15 papers · 4.8k · 1 hit paper · h-index 10

Impact in

    • Topic Modeling
    • Anomaly Detection Techniques and Applications
    • Neural Networks and Applications
    • Natural Language Processing Techniques
    • Time Series Analysis and Forecasting

Papers in

Klaus Greff

14 papers receiving 4.6k citations

Klaus Greff's Hit Papers

LSTM: A Search Space Odyssey 2016 · 4.4k citations
4.4k0+3+6Years since publication10002.0k3.0k4.0k

Peers

Klaus Greff
Comparison fields: 5 of 187
  • Artificial Intelligence 1.8k
  • Signal Processing 555
  • Computer Vision and Pattern Recognition 893
  • Management Science and Operations Research 361
  • Environmental Engineering 341
Replace Jan Koutník with:
Jan Koutník Switzerland
Bas R. Steunebrink Netherlands
Fred Cummins Ireland
Shanghang Zhang China
Felix A. Gers Switzerland
Claude Sammut Australia
Fuzhen Zhuang China
Davide Anguita Italy
Ting Liu China
Ruili Wang New Zealand
Klaus Greff relative to Jan Koutník Switzerland Jan Koutník's profile →
Citations per field
00.5×1.5×
Jan Koutník · 1×
Citations per year

Countries citing papers authored by Klaus Greff

Since Specialization
Citations

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

Fields of papers citing papers by Klaus Greff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Klaus Greff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Klaus Greff Line = papers co-authored together Klaus Greff links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
LSTM: A Search Space Odyssey
Hit paper breakdown →
20164435
2
33rd International Conference on Machine Learning, ICML 2016
2016113
3 202266
4
A Clockwork RNN
201456
5 201827
6
Scalable gradient-based tuning of continuous regularization hyperparameters
201622
7 201720
8 201219
9
Multi-Object Representation Learning with Iterative Variational Inference
201913
10 20129
11 20236
12
Unconventional computing using evolution-in-nanomaterio: neural networks meet nanoparticle networks
20162
13
Using neural networks to predict the functionality of reconfigurable nano-material networks
20171
14 20231
15 20250

About Klaus Greff

Klaus Greff is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Electrical and Electronic Engineering and Materials Chemistry, having authored 15 papers that have together received 4.8k indexed citations. Recurring topics across this work include Neural Networks and Applications (3 papers), Speech Recognition and Synthesis (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Vision and Imaging (3 papers), Music and Audio Processing (3 papers), Machine Learning in Materials Science (2 papers), Machine Learning and Data Classification (2 papers) and Advanced Memory and Neural Computing (2 papers). The work is most often cited by research in Artificial Intelligence (1.8k citations), Signal Processing (555 citations), Computer Vision and Pattern Recognition (893 citations), Management Science and Operations Research (361 citations) and Environmental Engineering (341 citations). Klaus Greff has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Jan Koutník, Jürgen Schmidhuber, Bas R. Steunebrink, Rupesh K. Srivastava, Mathias Berglund, Tapani Raiko, Jelena Luketina, Juergen Schmidhuber, Faustino Gomez and Sjoerd van Steenkiste. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Nature, IEEE Transactions on Neural Networks and Learning Systems, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).

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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