Mikołaj Bińkowski
- Economics and Econometrics
- Management Science and Operations Research
- Statistical and Nonlinear Physics
- Finance
- Artificial Intelligence
- Co-authors
- Frank NielsenArthur GrettonMichael ArbelDanica J. SutherlandCharles‐Albert LehalleAaron CourvilleYoshua BengioR Devon Hjelm
- Topics
- Complex Systems and Time Series Analysis (2 papers)Stock Market Forecasting Methods (2 papers)Time Series Analysis and Forecasting (1 paper)
- Journals
- The Journal of Portfolio ManagementSignals and communication technologyUCL Discovery (University College London)
- Partner nations
- United KingdomUnited Arab EmiratesJapan
In The Last Decade
Mikołaj Bińkowski
4 papers receiving 62 citations
Peers
Comparison fields: 5 of 25
- Economics and Econometrics 37
- Management Science and Operations Research 21
- Statistical and Nonlinear Physics 20
- Finance 18
- Artificial Intelligence 14
Countries citing papers authored by Mikołaj Bińkowski
This map shows the geographic impact of Mikołaj Bińkowski'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 Mikołaj Bińkowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikołaj Bińkowski more than expected).
Fields of papers citing papers by Mikołaj Bińkowski
This network shows the impact of papers produced by Mikołaj Bińkowski. 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 Mikołaj Bińkowski. The network helps show where Mikołaj Bińkowski may publish in the future.
Co-authorship network of co-authors of Mikołaj Bińkowski
This figure shows the co-authorship network connecting the top 25 collaborators of Mikołaj Bińkowski. A scholar is included among the top collaborators of Mikołaj Bińkowski 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 Mikołaj Bińkowski. Mikołaj Bińkowski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 56 | |
| 4 | On gradient regularizers for MMD GANs | 7 |
| 5 | Unsupervised one-to-many image translation | 1 |
About Mikołaj Bińkowski
Mikołaj Bińkowski is a scholar working on Management Science and Operations Research, Finance and Computer Vision and Pattern Recognition, having authored 5 papers that have together received 67 indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (2 papers), Stock Market Forecasting Methods (2 papers) and Time Series Analysis and Forecasting (1 paper). The work is most often cited by research in Finance (18 citations), Management Science and Operations Research (21 citations) and Statistical and Nonlinear Physics (20 citations). Mikołaj Bińkowski has collaborated with scholars based in United Kingdom, United Arab Emirates and Japan. Frequent co-authors include Frank Nielsen, Arthur Gretton, Michael Arbel, Danica J. Sutherland, Charles‐Albert Lehalle, Aaron Courville, Yoshua Bengio and R Devon Hjelm. Their work appears in journals such as The Journal of Portfolio Management, Signals and communication technology and UCL Discovery (University College London).
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.