Valentín Flunkert

2.8k citations
44 papers · 1.6k · 1 hit paper · h-index 21

Impact in

Papers in

Valentín Flunkert

44 papers receiving 1.5k citations

Valentín Flunkert's Hit Papers

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey 2022 · 179 citations
1790+1+2Years since publication50100150

Peers

Valentín Flunkert
Comparison fields: 5 of 110
  • Statistical and Nonlinear Physics 638
  • Computer Networks and Communications 842
  • Management Science and Operations Research 321
  • Signal Processing 256
  • Artificial Intelligence 274
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Countries citing papers authored by Valentín Flunkert

Since Specialization
Citations

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

Fields of papers citing papers by Valentín Flunkert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Valentín Flunkert, 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 Valentín Flunkert Line = papers co-authored together Valentín Flunkert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey
Hit paper breakdown →
2022179
2 2019145
3 2007138
4 2010121
5 2011100
6 201787
7
GluonTS: Probabilistic and Neural Time Series Modeling in Python
202082
8 200773
9 200957
10
Symmetry-breaking transitions in networks of nonlinear circuit elements
201650
11 202249
12
Probabilistic Forecasting with Spline Quantile Function RNNs
201948
13 201142
14 201342
15 200836
16
Bayesian intermittent demand forecasting for large inventories
201634
17 200933
18 201132
19 200930
20 201220

About Valentín Flunkert

Valentín Flunkert is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics, Signal Processing, Artificial Intelligence and Management Science and Operations Research, having authored 44 papers that have together received 1.6k indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (31 papers), Chaos control and synchronization (24 papers), stochastic dynamics and bifurcation (14 papers), Time Series Analysis and Forecasting (6 papers), Forecasting Techniques and Applications (5 papers), Stock Market Forecasting Methods (5 papers), Quantum chaos and dynamical systems (4 papers) and Semiconductor Lasers and Optical Devices (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (638 citations), Computer Networks and Communications (842 citations), Management Science and Operations Research (321 citations), Signal Processing (256 citations) and Artificial Intelligence (274 citations). Valentín Flunkert has collaborated with scholars based in Germany, Spain and United States. Frequent co-authors include Eckehard Schöll, Philipp Hövel, Jan Gasthaus, David Salinas, Tim Januschowski, Bernold Fiedler, Serhiy Yanchuk, Ingo Fischer, Laurent Callot and Thomas Dahms. Their work appears in journals such as Physical Review Letters, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, The European Physical Journal Special Topics, Chaos An Interdisciplinary Journal of Nonlinear Science and ACM Computing Surveys.

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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