Barnabás Póczos
Impact in
- Artificial Intelligence top 0.5%
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Sentiment Analysis and Opinion Mining
- Anomaly Detection Techniques and Applications
-
- Multimodal Machine Learning Applications
Papers in
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- Statistical Methods and Inference 16
- Advanced Statistical Methods and Models 12
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- Machine Learning and Algorithms 16
- Domain Adaptation and Few-Shot Learning 10
- Bayesian Methods and Mixture Models 10
- Neural Networks and Applications 9
- Co-authors
- Jeff SchneiderChunliang LiJaime CarbonellKirthevasan KandasamyZihang DaiZi-Rui WangHai PhamThomas Manzini
- Journals
- The Astrophysical Journal (3 papers)Monthly Notices of the Royal Astronomical Society (2 papers)Neurocomputing (2 papers)Journal of Machine Learning Research (2 papers)ACS Biomaterials Science & Engineering (1 paper)
- Partner nations
- United StatesHungaryCanada
In The Last Decade
Barnabás Póczos
114 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 164
- Artificial Intelligence 1.5k
- Computer Vision and Pattern Recognition 736
- Instrumentation 104
- Signal Processing 279
- Statistics and Probability 186
Countries citing papers authored by Barnabás Póczos
This map shows the geographic impact of Barnabás Póczos'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 Barnabás Póczos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Barnabás Póczos more than expected).
Fields of papers citing papers by Barnabás Póczos
This network shows the impact of papers produced by Barnabás Póczos. 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 Barnabás Póczos. The network helps show where Barnabás Póczos may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Barnabás Póczos, 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 | 2020 | 123 | |
| 2 | Differentiable Unrolled Alternating Direction Method of Multipliers for OneNet. | 2019 | 2 |
| 3 | Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments. | 2019 | 5 |
| 4 | Learning Local Search Heuristics for Boolean Satisfiability | 2019 | 25 |
| 5 | Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses | 2019 | 2 |
| 6 | A Flexible Multi-Objective Bayesian Optimization Approach using Random Scalarizations. | 2018 | 2 |
| 7 | Point Cloud GAN | 2018 | 7 |
| 8 | Parallelised Bayesian Optimisation via Thompson Sampling | 2018 | 44 |
| 9 | 2018 | 5 | |
| 10 | Classifier Two Sample Test for Video Anomaly Detections. | 2018 | 44 |
| 11 | Neural Architecture Search with Bayesian Optimisation and Optimal Transport | 2018 | 71 |
| 12 | Nonparametric Density Estimation under Adversarial Losses | 2018 | 3 |
| 13 | Hypothesis Transfer Learning via Transformation Functions | 2017 | 9 |
| 14 | High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models | 2016 | 28 |
| 15 | 2016 | 32 | |
| 16 | Utilize old coordinates: faster doubly stochastic gradients for kernel methods | 2016 | 2 |
| 17 | On variance reduction in stochastic gradient descent and its asynchronous variants | 2015 | 22 |
| 18 | 2015 | 51 | |
| 19 | Bayesian Active Learning for Posterior Estimation - IJCAI-15 Distinguished Paper. | 2015 | 1 |
| 20 | Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions. | 2014 | 4 |
About Barnabás Póczos
Barnabás Póczos is a scholar working on Statistics and Probability, Artificial Intelligence, Computational Mathematics, Signal Processing and Computer Vision and Pattern Recognition, having authored 120 papers that have together received 3.3k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (16 papers), Statistical Methods and Inference (16 papers), Sparse and Compressive Sensing Techniques (13 papers), Blind Source Separation Techniques (12 papers), Advanced Statistical Methods and Models (12 papers), Domain Adaptation and Few-Shot Learning (10 papers), Bayesian Methods and Mixture Models (10 papers) and Neural Networks and Applications (9 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Computer Vision and Pattern Recognition (736 citations), Instrumentation (104 citations), Signal Processing (279 citations) and Statistics and Probability (186 citations). Barnabás Póczos has collaborated with scholars based in United States, Hungary and Canada. Frequent co-authors include Jeff Schneider, Chunliang Li, Jaime Carbonell, Kirthevasan Kandasamy, Zihang Dai, Zi-Rui Wang, Hai Pham, Thomas Manzini, Paul Pu Liang and Siamak Ravanbakhsh. Their work appears in journals such as The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society, Neurocomputing, Journal of Machine Learning Research and ACS Biomaterials Science & Engineering.
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.