Thomas Kipf
Impact in
-
- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
- Video Surveillance and Tracking Methods
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Anomaly Detection Techniques and Applications
- Domain Adaptation and Few-Shot Learning
Papers in
-
- Domain Adaptation and Few-Shot Learning 3
-
- Multimodal Machine Learning Applications 3
- Advanced Image and Video Retrieval Techniques 2
- Co-authors
- Max Welling (2 shared papers)Ethan Fetaya (1 shared paper)Kuan-Chieh Wang (1 shared paper)Richard S. Zemel (1 shared paper)Peter Boncz (2 shared papers)Viktor Leis (2 shared papers)Andreas Kipf (2 shared papers)Bernhard Radke (2 shared papers)
- Journals
- Data Archiving and Networked Services (DANS) (1 paper)UvA-DARE (University of Amsterdam) (2 papers)Zenodo (CERN European Organization for Nuclear Research) (1 paper)Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands (2 papers)Neural Information Processing Systems (1 paper)
- Partner nations
- NetherlandsGermanyUnited States
In The Last Decade
Thomas Kipf
10 papers receiving 174 citations
Peers
Comparison fields: 5 of 45
- Computer Vision and Pattern Recognition 87
- Artificial Intelligence 120
- Signal Processing 32
- Computer Graphics and Computer-Aided Design 5
- Automotive Engineering 15
Countries citing papers authored by Thomas Kipf
This map shows the geographic impact of Thomas Kipf'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 Thomas Kipf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Kipf more than expected).
Fields of papers citing papers by Thomas Kipf
This network shows the impact of papers produced by Thomas Kipf. 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 Thomas Kipf. The network helps show where Thomas Kipf may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Kipf, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Neural Relational Inference for Interacting Systems | 2018 | 92 |
| 2 | 2019 | 21 | |
| 3 | Deep learning with graph-structured representations | 2020 | 16 |
| 4 | Contrastive Learning of Structured World Models | 2020 | 15 |
| 5 | Learned Cardinalities: Estimating Correlated Joins with Deep Learning | 2018 | 14 |
| 6 | Object-Centric Learning with Slot Attention | 2020 | 13 |
| 7 | 2023 | 6 | |
| 8 | 2023 | 4 | |
| 9 | 2018 | 2 | |
| 10 | 2023 | 1 |
About Thomas Kipf
Thomas Kipf is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computer Networks and Communications and Statistical and Nonlinear Physics, having authored 10 papers that have together received 184 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Data Management and Algorithms (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Complex Network Analysis Techniques (1 paper), Speech and Audio Processing (1 paper), Time Series Analysis and Forecasting (1 paper) and 3D Shape Modeling and Analysis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (87 citations), Artificial Intelligence (120 citations), Signal Processing (32 citations), Computer Graphics and Computer-Aided Design (5 citations) and Automotive Engineering (15 citations). Thomas Kipf has collaborated with scholars based in Netherlands, Germany and United States. Frequent co-authors include Max Welling, Ethan Fetaya, Kuan-Chieh Wang, Richard S. Zemel, Peter Boncz, Viktor Leis, Andreas Kipf, Bernhard Radke, Elise van der Pol and Alfons Kemper. Their work appears in journals such as Data Archiving and Networked Services (DANS), UvA-DARE (University of Amsterdam), Zenodo (CERN European Organization for Nuclear Research), Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands and Neural Information Processing Systems.
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.