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
- Video Surveillance and Tracking Methods
- Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning
Papers in
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- Evolutionary Algorithms and Applications 2
- Machine Learning and Algorithms 2
- Metaheuristic Optimization Algorithms Research 2
- Domain Adaptation and Few-Shot Learning 1
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- Advanced Multi-Objective Optimization Algorithms 3
- Co-authors
- Dumitru Erhan (1 shared paper)Konstantinos Bousmalis (1 shared paper)Nathan Silberman (1 shared paper)Dilip Krishnan (1 shared paper)Thomas Funkhouser (1 shared paper)Lucy J. Colwell (3 shared papers)David Belanger (2 shared papers)Kevin J. Murphy (2 shared papers)
- Journals
- International Conference on Learning Representations (1 paper)Uncertainty in Artificial Intelligence (1 paper)Proceedings of the Genetic and Evolutionary Computation Conference Companion (1 paper)arXiv (Cornell University) (1 paper)International Conference on Machine Learning (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
David Dohan
9 papers receiving 977 citations
David Dohan's Hit Papers
Peers
Comparison fields: 5 of 85
- Computer Vision and Pattern Recognition 700
- Artificial Intelligence 548
- Media Technology 71
- Computer Graphics and Computer-Aided Design 22
- Radiology, Nuclear Medicine and Imaging 132
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 24 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 | 942 |
| 2 | 2015 | 21 | |
| 3 | Model-based reinforcement learning for biological sequence design | 2020 | 19 |
| 4 | 2020 | 8 | |
| 5 | 2021 | 6 | |
| 6 | Amortized Bayesian Optimization over Discrete Spaces | 2020 | 4 |
| 7 | K-median Algorithms: Theory in Practice | 2015 | 4 |
| 8 | Latent Programmer: Discrete Latent Codes for Program Synthesis | 2021 | 1 |
| 9 | 2018 | 1 | |
| 10 | 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 10 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (3 papers), Multimodal Machine Learning Applications (2 papers), Evolutionary Algorithms and Applications (2 papers), Machine Learning and Algorithms (2 papers), Metaheuristic Optimization Algorithms Research (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Machine Learning in Bioinformatics (1 paper) and Web Application Security Vulnerabilities (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (700 citations), Artificial Intelligence (548 citations), Media Technology (71 citations), Computer Graphics and Computer-Aided Design (22 citations) and Radiology, Nuclear Medicine and Imaging (132 citations). David Dohan has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Dumitru Erhan, Konstantinos Bousmalis, Nathan Silberman, Dilip Krishnan, Thomas Funkhouser, Lucy J. Colwell, David Belanger, Kevin J. Murphy, Christof Angermueller and Kevin Murphy. Their work appears in journals such as International Conference on Learning Representations, Uncertainty in Artificial Intelligence, Proceedings of the Genetic and Evolutionary Computation Conference Companion, arXiv (Cornell University) and International Conference on Machine Learning.
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.