David Dohan
Impact in
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- Multimodal Machine Learning Applications
- Advanced Neural Network Applications
- Generative Adversarial Networks and Image Synthesis
- Advanced Image Processing Techniques
- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning
Papers in
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- Metaheuristic Optimization Algorithms Research 2
- Machine Learning and Algorithms 2
- Evolutionary Algorithms and Applications 2
- Domain Adaptation and Few-Shot Learning 1
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- Advanced Multi-Objective Optimization Algorithms 3
- Co-authors
- Nathan Silberman (1 shared paper)Dumitru Erhan (1 shared paper)Dilip Krishnan (1 shared paper)Konstantinos Bousmalis (1 shared paper)Thomas Funkhouser (1 shared paper)Lucy J. Colwell (3 shared papers)David Belanger (2 shared papers)Christof Angermueller (2 shared papers)
- Journals
- International Conference on Machine Learning (1 paper)International Conference on Learning Representations (1 paper)Proceedings of the Genetic and Evolutionary Computation Conference Companion (1 paper)arXiv (Cornell University) (1 paper)Uncertainty in Artificial Intelligence (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
David Dohan
11 papers receiving 1.1k citations
David Dohan's Hit Papers
Peers
Comparison fields: 5 of 85
- Computer Vision and Pattern Recognition 791
- Artificial Intelligence 609
- Media Technology 75
- Radiology, Nuclear Medicine and Imaging 152
- Computer Graphics and Computer-Aided Design 25
Countries citing papers authored by David Dohan
This map shows the geographic impact of David Dohan'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 David Dohan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Dohan more than expected).
Fields of papers citing papers by David Dohan
This network shows the impact of papers produced by David Dohan. 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 David Dohan. The network helps show where David Dohan may publish in the future.
Co-authors
The 25 scholars most cited alongside David Dohan, 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 | Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks Hit paper breakdown → | 2017 | 1065 |
| 2 | 2015 | 21 | |
| 3 | Model-based reinforcement learning for biological sequence design | 2020 | 19 |
| 4 | 2020 | 8 | |
| 5 | 2021 | 8 | |
| 6 | K-median Algorithms: Theory in Practice | 2015 | 5 |
| 7 | Amortized Bayesian Optimization over Discrete Spaces | 2020 | 4 |
| 8 | 2023 | 2 | |
| 9 | Latent Programmer: Discrete Latent Codes for Program Synthesis | 2021 | 1 |
| 10 | 2018 | 1 | |
| 11 | 2022 | 1 | |
| 12 | EXPLORING NEURAL ARCHITECTURE SEARCH FOR LANGUAGE TASKS | 2018 | 0 |
About David Dohan
David Dohan is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Molecular Biology and Information Systems, having authored 12 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (3 papers), Multimodal Machine Learning Applications (2 papers), Metaheuristic Optimization Algorithms Research (2 papers), Machine Learning and Algorithms (2 papers), Evolutionary Algorithms and Applications (2 papers), Web Application Security Vulnerabilities (1 paper), RNA and protein synthesis mechanisms (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (791 citations), Artificial Intelligence (609 citations), Media Technology (75 citations), Radiology, Nuclear Medicine and Imaging (152 citations) and Computer Graphics and Computer-Aided Design (25 citations). David Dohan has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Nathan Silberman, Dumitru Erhan, Dilip Krishnan, Konstantinos Bousmalis, Thomas Funkhouser, Lucy J. Colwell, David Belanger, Christof Angermueller, Kevin J. Murphy and Maxwell L. Bileschi. Their work appears in journals such as International Conference on Machine Learning, International Conference on Learning Representations, Proceedings of the Genetic and Evolutionary Computation Conference Companion, arXiv (Cornell University) and Uncertainty in Artificial Intelligence.
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.