Folgen
David Dohan
David Dohan
Google Brain
Bestätigte E-Mail-Adresse bei google.com
Titel
Zitiert von
Zitiert von
Jahr
Palm: Scaling language modeling with pathways
A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ...
Journal of Machine Learning Research 24 (240), 1-113, 2023
37722023
Unsupervised pixel-level domain adaptation with generative adversarial networks
K Bousmalis, N Silberman, D Dohan, D Erhan, D Krishnan
Proceedings of the IEEE conference on computer vision and pattern …, 2017
18612017
Gpt-4 technical report
J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ...
arXiv preprint arXiv:2303.08774, 2023
15672023
Rethinking attention with performers
K Choromanski, V Likhosherstov, D Dohan, X Song, A Gane, T Sarlos, ...
International Conference on Learning Representations, 2021
13752021
Qanet: Combining local convolution with global self-attention for reading comprehension
AW Yu, D Dohan, MT Luong, R Zhao, K Chen, M Norouzi, QV Le
International Conference on Learning Representations, 2018
1294*2018
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...
arXiv preprint arXiv:2206.04615, 2022
8162022
Program synthesis with large language models
J Austin, A Odena, M Nye, M Bosma, H Michalewski, D Dohan, E Jiang, ...
arXiv preprint arXiv:2108.07732, 2021
7502021
Solving quantitative reasoning problems with language models
A Lewkowycz, A Andreassen, D Dohan, E Dyer, H Michalewski, ...
Advances in Neural Information Processing Systems 35, 3843-3857, 2022
4412022
Show your work: Scratchpads for intermediate computation with language models
M Nye, AJ Andreassen, G Gur-Ari, H Michalewski, J Austin, D Bieber, ...
arXiv preprint arXiv:2112.00114, 2021
4272021
Large language models can be easily distracted by irrelevant context
F Shi, X Chen, K Misra, N Scales, D Dohan, EH Chi, N Schärli, D Zhou
International Conference on Machine Learning, 31210-31227, 2023
1572023
Model-based reinforcement learning for biological sequence design
C Angermueller, D Dohan, D Belanger, R Deshpande, K Murphy, ...
International conference on learning representations, 2019
1252019
Masked language modeling for proteins via linearly scalable long-context transformers
K Choromanski, V Likhosherstov, D Dohan, X Song, A Gane, T Sarlos, ...
arXiv preprint arXiv:2006.03555, 2020
892020
Palm: Scaling language modeling with pathways. arXiv 2022
A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ...
arXiv preprint arXiv:2204.02311 10, 2022
832022
Language model cascades
D Dohan, W Xu, A Lewkowycz, J Austin, D Bieber, RG Lopes, Y Wu, ...
arXiv preprint arXiv:2207.10342, 2022
652022
Chi, Nathanael Schärli, and Denny Zhou. 2023. Large language models can be easily distracted by irrelevant context
F Shi, X Chen, K Misra, N Scales, D Dohan
arXiv preprint arXiv:2302.00093, 2023
622023
Population-based black-box optimization for biological sequence design
C Angermueller, D Belanger, A Gane, Z Mariet, D Dohan, K Murphy, ...
International conference on machine learning, 324-334, 2020
492020
Is transfer learning necessary for protein landscape prediction?
A Shanehsazzadeh, D Belanger, D Dohan
NeurIPS workshop on Machine Learning in Structural Biology, 2020
482020
Learning hierarchical semantic segmentations of LIDAR data
D Dohan, B Matejek, T Funkhouser
2015 International Conference on 3D Vision, 273-281, 2015
442015
Evoprompting: Language models for code-level neural architecture search
A Chen, D Dohan, D So
Advances in Neural Information Processing Systems 36, 2024
432024
Towards learning universal hyperparameter optimizers with transformers
Y Chen, X Song, C Lee, Z Wang, R Zhang, D Dohan, K Kawakami, ...
Advances in Neural Information Processing Systems 35, 32053-32068, 2022
392022
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20