Valentín Flunkert

2.7k citations
35 papers · 1.3k · 1 hit paper · h-index 19

Impact in

Papers in

Valentín Flunkert

35 papers receiving 1.2k citations

Valentín Flunkert's Hit Papers

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey 2022 · 150 citations
1500+1+2Years since publication50100150

Peers

Valentín Flunkert
Comparison fields: 5 of 106
  • Statistical and Nonlinear Physics 521
  • Computer Networks and Communications 714
  • Management Science and Operations Research 269
  • Signal Processing 219
  • Artificial Intelligence 226
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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 35 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 →
2022150
2 2007124
3 2019117
4 2010111
5 201193
6 201778
7
GluonTS: Probabilistic and Neural Time Series Modeling in Python
202071
8 200765
9 200953
10
Probabilistic Forecasting with Spline Quantile Function RNNs
201943
11 202241
12 201338
13
Bayesian intermittent demand forecasting for large inventories
201634
14 201134
15 201129
16 200829
17 200929
18 200923
19 201219
20 200718

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 35 papers that have together received 1.3k indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (24 papers), Chaos control and synchronization (18 papers), stochastic dynamics and bifurcation (11 papers), Time Series Analysis and Forecasting (6 papers), Forecasting Techniques and Applications (5 papers), Stock Market Forecasting Methods (5 papers), Neural Networks Stability and Synchronization (4 papers) and Quantum optics and atomic interactions (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (521 citations), Computer Networks and Communications (714 citations), Management Science and Operations Research (269 citations), Signal Processing (219 citations) and Artificial Intelligence (226 citations). Valentín Flunkert has collaborated with scholars based in Germany, Spain and United Kingdom. Frequent co-authors include Eckehard Schöll, Philipp Hövel, Jan Gasthaus, David Salinas, Tim Januschowski, Bernold Fiedler, Serhiy Yanchuk, Ingo Fischer, Laurent Callot and Syama Sundar Rangapuram. Their work appears in journals such as Physical Review Letters, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Chaos An Interdisciplinary Journal of Nonlinear Science, The European Physical Journal Special Topics and Proceedings of the VLDB Endowment.

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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