Barnabás Póczos
Impact in
- Artificial Intelligence top 0.5%
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
- Sentiment Analysis and Opinion Mining
- Anomaly Detection Techniques and Applications
-
- Multimodal Machine Learning Applications
Papers in
-
- Machine Learning and Algorithms 17
- Neural Networks and Applications 13
- Domain Adaptation and Few-Shot Learning 11
- Bayesian Methods and Mixture Models 11
- Co-authors
- Jeff Schneider (37 shared papers)András Lörincz (21 shared papers)Chunliang Li (9 shared papers)Jaime Carbonell (2 shared papers)Zihang Dai (1 shared paper)Zi-Rui Wang (1 shared paper)Kirthevasan Kandasamy (13 shared papers)Hai Pham (4 shared papers)
- Journals
- The Astrophysical Journal (3 papers)Neurocomputing (2 papers)Journal of Machine Learning Research (2 papers)Monthly Notices of the Royal Astronomical Society (2 papers)Bioinformatics (1 paper)
- Partner nations
- United StatesHungaryCanada
In The Last Decade
Barnabás Póczos
128 papers receiving 3.7k citations
Barnabás Póczos's Hit Papers
Peers
Comparison fields: 5 of 164
- Artificial Intelligence 1.7k
- Computer Vision and Pattern Recognition 831
- Signal Processing 370
- Instrumentation 109
- Computational Mathematics 15
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-authors
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
Showing the 20 most-cited of 135 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Characterizing and Avoiding Negative Transfer Hit paper breakdown → | 2019 | 305 |
| 2 | Found in Translation: Learning Robust Joint Representations by Cyclic Translations between Modalities Hit paper breakdown → | 2019 | 297 |
| 3 | 2019 | 189 | |
| 4 | 2017 | 160 | |
| 5 | Deep Sets | 2017 | 134 |
| 6 | 2020 | 130 | |
| 7 | 2019 | 129 | |
| 8 | 2017 | 118 | |
| 9 | 2019 | 110 | |
| 10 | 2016 | 108 | |
| 11 | 2019 | 92 | |
| 12 | 2020 | 91 | |
| 13 | Neural Architecture Search with Bayesian Optimisation and Optimal Transport | 2018 | 77 |
| 14 | MMD GAN: Towards Deeper Understanding of Moment Matching Network | 2017 | 64 |
| 15 | 2019 | 62 | |
| 16 | 2010 | 60 | |
| 17 | 2018 | 58 | |
| 18 | 2015 | 54 | |
| 19 | Parallelised Bayesian Optimisation via Thompson Sampling | 2018 | 51 |
| 20 | 2018 | 50 |
About Barnabás Póczos
Barnabás Póczos is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Statistics and Probability and Computational Mechanics, having authored 135 papers that have together received 3.8k indexed citations. Recurring topics across this work include Blind Source Separation Techniques (18 papers), Machine Learning and Algorithms (17 papers), Statistical Methods and Inference (16 papers), Sparse and Compressive Sensing Techniques (13 papers), Neural Networks and Applications (13 papers), Advanced Statistical Methods and Models (12 papers), Domain Adaptation and Few-Shot Learning (11 papers) and Bayesian Methods and Mixture Models (11 papers). The work is most often cited by research in Artificial Intelligence (1.7k citations), Computer Vision and Pattern Recognition (831 citations), Signal Processing (370 citations), Instrumentation (109 citations) and Computational Mathematics (15 citations). Barnabás Póczos has collaborated with scholars based in United States, Hungary and Canada. Frequent co-authors include Jeff Schneider, András Lörincz, Chunliang Li, Jaime Carbonell, Zihang Dai, Zi-Rui Wang, Kirthevasan Kandasamy, Hai Pham, Siamak Ravanbakhsh and Paul Pu Liang. Their work appears in journals such as The Astrophysical Journal, Neurocomputing, Journal of Machine Learning Research, Monthly Notices of the Royal Astronomical Society and Bioinformatics.
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.