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ORCIDDavid Dohan
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2020 – today
- 2020
[c8]Christof Angermüller, David Dohan, David Belanger, Ramya Deshpande, Kevin Murphy, Lucy Colwell:
Model-based reinforcement learning for biological sequence design. ICLR 2020- [c7]Christof Angermüller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy Colwell, D. Sculley:
Population-Based Black-Box Optimization for Biological Sequence Design. ICML 2020: 324-334 - [c6]Kevin Swersky, Yulia Rubanova, David Dohan, Kevin Murphy:
Amortized Bayesian Optimization over Discrete Spaces. UAI 2020: 769-778 - [i8]Christof Angermüller, David Belanger, Andreea Gane, Zelda Mariet, David Dohan, Kevin Murphy, Lucy Colwell, D. Sculley:
Population-Based Black-Box Optimization for Biological Sequence Design. CoRR abs/2006.03227 (2020) - [i7]Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Jared Davis, Tamás Sarlós, David Belanger, Lucy Colwell, Adrian Weller:
Masked Language Modeling for Proteins via Linearly Scalable Long-Context Transformers. CoRR abs/2006.03555 (2020) - [i6]Krzysztof Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamás Sarlós, Peter Hawkins, Jared Davis, Afroz Mohiuddin, Lukasz Kaiser, David Belanger, Lucy Colwell, Adrian Weller:
Rethinking Attention with Performers. CoRR abs/2009.14794 (2020) - [i5]Amir Shanehsazzadeh, David Belanger, David Dohan:
Fixed-Length Protein Embeddings using Contextual Lenses. CoRR abs/2010.15065 (2020) - [i4]Amir Shanehsazzadeh, David Belanger, David Dohan:
Is Transfer Learning Necessary for Protein Landscape Prediction? CoRR abs/2011.03443 (2020) - [i3]Joey Hong, David Dohan, Rishabh Singh, Charles Sutton, Manzil Zaheer:
Latent Programmer: Discrete Latent Codes for Program Synthesis. CoRR abs/2012.00377 (2020)
2010 – 2019
- 2018
- [c5]David Dohan, David R. So, Quoc V. Le:
Evolving modular neural sequence architectures with genetic programming. GECCO (Companion) 2018: 37-38 - [c4]Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, Quoc V. Le:
QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension. ICLR (Poster) 2018 - [i2]Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, Quoc V. Le:
QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension. CoRR abs/1804.09541 (2018) - 2017
- [c3]Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan:
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. CVPR 2017: 95-104 - 2016
- [i1]Konstantinos Bousmalis, Nathan Silberman, David Dohan, Dumitru Erhan, Dilip Krishnan:
Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks. CoRR abs/1612.05424 (2016) - 2015
- [c2]David Dohan, Brian Matejek, Thomas A. Funkhouser:
Learning Hierarchical Semantic Segmentations of LIDAR Data. 3DV 2015: 273-281
1990 – 1999
- 1998
- [c1]David Dohan:
The wonder of it all. SIGGRAPH Abstracts and Applications 1998: 332
Coauthor Index
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