Manfred Opper
- Artificial Intelligence top 0.2%
- Neural Networks and Applications 51
- Gaussian Processes and Bayesian Inference 49
- Machine Learning and Algorithms 20
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- Statistical Mechanics and Entropy 20
- Model Reduction and Neural Networks 15
- Signal Processing top 1%
- Statistics and Probability top 1%
- Markov Chains and Monte Carlo Methods 15
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- Theoretical and Computational Physics 22
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- Control Systems and Identification 18
- Co-authors
- Haim SompolinskyH. Sebastian SeungLehel CsatóOle WintherGuido SanguinettiS. DiederichDavid HausslerDavid Saad
- Journals
- Physical Review Letters (15 papers)Physical review. E (5 papers)Journal of Machine Learning Research (5 papers)
- Partner nations
- GermanyUnited KingdomDenmark
In The Last Decade
Manfred Opper
153 papers receiving 4.9k citations
Hit Papers
Peers
Comparison fields: 5 of 166
- Artificial Intelligence 3.3k
- Statistical and Nonlinear Physics 693
- Signal Processing 513
- Statistics and Probability 351
- Computer Vision and Pattern Recognition 732
Countries citing papers authored by Manfred Opper
This map shows the geographic impact of Manfred Opper'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 Manfred Opper with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manfred Opper more than expected).
Fields of papers citing papers by Manfred Opper
This network shows the impact of papers produced by Manfred Opper. 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 Manfred Opper. The network helps show where Manfred Opper may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Manfred Opper, 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 | 3 | |
| 2 | 2022 | 2 | |
| 3 | 2021 | 4 | |
| 4 | Perturbative Black Box Variational Inference | 2017 | 3 |
| 5 | A tractable approximation to optimal point process filtering: application to neural encoding | 2015 | 1 |
| 6 | Approximate Gaussian process inference for the drift of stochastic differential equations | 2013 | 3 |
| 7 | Approximate Gaussian process inference for the drift function in stochastic differential equations | 2013 | 14 |
| 8 | Bayesian Inference for Change Points in Dynamical Systems with Reusable States - a Chinese Restaurant Process Approach | 2012 | 6 |
| 9 | Analytical Results for the Error in Filtering of Gaussian Processes | 2011 | 2 |
| 10 | Perturbation Corrections in Approximate Inference: Mixture Modelling Applications | 2009 | 5 |
| 11 | Improving on Expectation Propagation | 2008 | 7 |
| 12 | Variational inference for Markov jump processes | 2007 | 30 |
| 13 | Variational Linear Response | 2003 | 3 |
| 14 | Approximate Analytical Bootstrap Averages for Support Vector Classifiers | 2003 | 3 |
| 15 | An approximate analytical approach to resampling averages | 2003 | 6 |
| 16 | A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages | 2002 | 4 |
| 17 | Continuous Drifting Games | 2000 | 3 |
| 18 | Advances in large margin classifiers | 2000 | 10 |
| 19 | A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks | 1996 | 5 |
| 20 | 1991 | 32 |
About Manfred Opper
Manfred Opper is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Statistics and Probability, Condensed Matter Physics and Statistics, Probability and Uncertainty, having authored 155 papers that have together received 5.3k indexed citations. Recurring topics across this work include Neural Networks and Applications (51 papers), Gaussian Processes and Bayesian Inference (49 papers), Theoretical and Computational Physics (22 papers), Machine Learning and Algorithms (20 papers), Statistical Mechanics and Entropy (20 papers), Control Systems and Identification (18 papers), Model Reduction and Neural Networks (15 papers) and Markov Chains and Monte Carlo Methods (15 papers). The work is most often cited by research in Artificial Intelligence (3.3k citations), Statistical and Nonlinear Physics (693 citations), Signal Processing (513 citations), Statistics and Probability (351 citations) and Computer Vision and Pattern Recognition (732 citations). Manfred Opper has collaborated with scholars based in Germany, United Kingdom and Denmark. Frequent co-authors include Haim Sompolinsky, H. Sebastian Seung, Lehel Csató, Ole Winther, Guido Sanguinetti, S. Diederich, David Haussler, David Saad, Botond Cseke and Cédric Archambeau. Their work appears in journals such as Physical Review Letters, Physical review. E, Journal of Machine Learning Research, Physica A Statistical Mechanics and its Applications and Neural Computation.
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.