David Dohan
Impact in
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- Multimodal Machine Learning Applications
- Generative Adversarial Networks and Image Synthesis
- Advanced Neural Network Applications
- 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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- Machine Learning and Algorithms 2
- Machine Learning and Data Classification 1
- Evolutionary Algorithms and Applications 1
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- Advanced Multi-Objective Optimization Algorithms 2
- Co-authors
- Dilip Krishnan (1 shared paper)Dumitru Erhan (1 shared paper)Konstantinos Bousmalis (1 shared paper)Nathan Silberman (1 shared paper)Thomas A. Funkhouser (1 shared paper)Kevin J. Murphy (2 shared papers)Lucy J. Colwell (2 shared papers)Christof Angermueller (1 shared paper)
- Journals
- Uncertainty in Artificial Intelligence (1 paper)International Conference on Learning Representations (1 paper)Proceedings of the Genetic and Evolutionary Computation Conference Companion (1 paper)International Conference on Machine Learning (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
David Dohan
10 papers receiving 1.2k citations
David Dohan's Hit Papers
Peers
Comparison fields: 5 of 89
- Computer Vision and Pattern Recognition 870
- Artificial Intelligence 675
- Media Technology 75
- Radiology, Nuclear Medicine and Imaging 171
- Computer Graphics and Computer-Aided Design 30
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 | 1165 |
| 2 | 2015 | 24 | |
| 3 | Model-based reinforcement learning for biological sequence design | 2020 | 20 |
| 4 | 2021 | 8 | |
| 5 | 2023 | 6 | |
| 6 | Amortized Bayesian Optimization over Discrete Spaces | 2020 | 5 |
| 7 | K-median Algorithms: Theory in Practice | 2015 | 5 |
| 8 | 2022 | 4 | |
| 9 | Latent Programmer: Discrete Latent Codes for Program Synthesis | 2021 | 1 |
| 10 | 2018 | 1 | |
| 11 | 2023 | 0 | |
| 12 | 2022 | 0 | |
| 13 | 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, Computer Graphics and Computer-Aided Design and Software, having authored 13 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (2 papers), Machine Learning and Algorithms (2 papers), Multimodal Machine Learning Applications (2 papers), Machine Learning and Data Classification (1 paper), Software Engineering Research (1 paper), Web Application Security Vulnerabilities (1 paper), Evolutionary Algorithms and Applications (1 paper) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (870 citations), Artificial Intelligence (675 citations), Media Technology (75 citations), Radiology, Nuclear Medicine and Imaging (171 citations) and Computer Graphics and Computer-Aided Design (30 citations). David Dohan has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Dilip Krishnan, Dumitru Erhan, Konstantinos Bousmalis, Nathan Silberman, Thomas A. Funkhouser, Kevin J. Murphy, Lucy J. Colwell, Christof Angermueller, David Belanger and David B. Belanger. Their work appears in journals such as Uncertainty in Artificial Intelligence, International Conference on Learning Representations, Proceedings of the Genetic and Evolutionary Computation Conference Companion 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.