Volker Tresp
Impact in
- Computational Mathematics top 0.5%
- Artificial Intelligence top 0.1%
- Advanced Graph Neural Networks
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
- Semantic Web and Ontologies
- Gaussian Processes and Bayesian Inference
Papers in
-
- Advanced Graph Neural Networks 34
- Topic Modeling 31
- Neural Networks and Applications 27
- Semantic Web and Ontologies 23
- Gaussian Processes and Bayesian Inference 16
- Bayesian Modeling and Causal Inference 14
- Co-authors
- Maximilian NickelTodd K. LeenThomas G. DietterichHans‐Peter KriegelKai YuAnton SchwaighoferKevin MurphyEvgeniy Gabrilovich
- Journals
- Neural Computation (4 papers)Journal of Web Semantics (3 papers)Proceedings of the IEEE (3 papers)Machine Learning (2 papers)Data Mining and Knowledge Discovery (2 papers)
- Partner nations
- GermanyUnited StatesItaly
In The Last Decade
Volker Tresp
186 papers receiving 7.8k citations
Hit Papers
Peers
Comparison fields: 5 of 193
- Computational Mathematics 182
- Artificial Intelligence 5.7k
- Computer Vision and Pattern Recognition 1.8k
- Management Science and Operations Research 806
- Signal Processing 605
Countries citing papers authored by Volker Tresp
This map shows the geographic impact of Volker Tresp'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 Volker Tresp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Volker Tresp more than expected).
Fields of papers citing papers by Volker Tresp
This network shows the impact of papers produced by Volker Tresp. 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 Volker Tresp. The network helps show where Volker Tresp may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Volker Tresp, 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 | 2024 | 0 | |
| 2 | 2021 | 8 | |
| 3 | Explainable Subgraph Reasoning for Forecasting on Temporal Knowledge Graphs | 2021 | 54 |
| 4 | 2020 | 42 | |
| 5 | Holistic Representations for Memorization and Inference | 2018 | 8 |
| 6 | Reducing the Rank in Relational Factorization Models by Including Observable Patterns | 2014 | 31 |
| 7 | A Three-Way Model for Collective Learning on Multi-Relational Data Hit paper breakdown → | 2011 | 905 |
| 8 | Multi-relational learning with Gaussian processes | 2009 | 21 |
| 9 | Evaluating some Feature Selection Methods for an Improved SVM Classifier | 2008 | 2 |
| 10 | Learning Gaussian Process Kernels via Hierarchical Bayes | 2004 | 112 |
| 11 | GPPS: A Gaussian Process Positioning System for Cellular Networks | 2003 | 101 |
| 12 | Transductive and Inductive Methods for Approximate Gaussian Process Regression | 2002 | 42 |
| 13 | The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging | 2002 | 5 |
| 14 | Mixtures of Gaussian Processes | 2000 | 116 |
| 15 | Call-Based Fraud Detection in Mobile Communication Networks Using a Hierarchical Regime-Switching Model | 1998 | 30 |
| 16 | Die besonderen Eigenschaften Neuronaler Netze bei der Approximation von Funktionen. | 1995 | 2 |
| 17 | Improved Gaussian Mixture Density Estimates Using Bayesian Penalty Terms and Network Averaging | 1995 | 44 |
| 18 | Discovering Structure in Continuous Variables Using Bayesian Networks | 1995 | 30 |
| 19 | Some Solutions to the Missing Feature Problem in Vision | 1992 | 58 |
| 20 | Network Structuring and Training Using Rule-based Knowledge | 1992 | 53 |
About Volker Tresp
Volker Tresp is a scholar working on Computational Mathematics, Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition and Health Informatics, having authored 194 papers that have together received 8.3k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (34 papers), Topic Modeling (31 papers), Neural Networks and Applications (27 papers), Semantic Web and Ontologies (23 papers), Gaussian Processes and Bayesian Inference (16 papers), Bayesian Modeling and Causal Inference (14 papers), Multimodal Machine Learning Applications (13 papers) and Recommender Systems and Techniques (12 papers). The work is most often cited by research in Computational Mathematics (182 citations), Artificial Intelligence (5.7k citations), Computer Vision and Pattern Recognition (1.8k citations), Management Science and Operations Research (806 citations) and Signal Processing (605 citations). Volker Tresp has collaborated with scholars based in Germany, United States and Italy. Frequent co-authors include Maximilian Nickel, Todd K. Leen, Thomas G. Dietterich, Hans‐Peter Kriegel, Kai Yu, Anton Schwaighofer, Kevin Murphy, Evgeniy Gabrilovich, Shipeng Yu and Yunpu Ma. Their work appears in journals such as Neural Computation, Journal of Web Semantics, Proceedings of the IEEE, Machine Learning and Data Mining and Knowledge Discovery.
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.