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David Belanger
David Belanger
Research Scientist, Google Brain
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Rethinking attention with performers
K Choromanski, V Likhosherstov, D Dohan, X Song, A Gane, T Sarlos, ...
arXiv preprint arXiv:2009.14794, 2020
16812020
Fast and accurate entity recognition with iterated dilated convolutions
E Strubell, P Verga, D Belanger, A McCallum
arXiv preprint arXiv:1702.02098, 2017
5832017
Sequential regulatory activity prediction across chromosomes with convolutional neural networks
DR Kelley, YA Reshef, M Bileschi, D Belanger, CY McLean, J Snoek
Genome research 28 (5), 739-750, 2018
4782018
Ask the GRU Multi-task Learning for Deep Text Recommendations
T Bansal, D Belanger, A McCallum
proceedings of the 10th ACM Conference on Recommender Systems, 107-114, 2016
3902016
Chains of reasoning over entities, relations, and text using recurrent neural networks
R Das, A Neelakantan, D Belanger, A McCallum
arXiv preprint arXiv:1607.01426, 2016
3402016
Using deep learning to annotate the protein universe
ML Bileschi, D Belanger, DH Bryant, T Sanderson, B Carter, D Sculley, ...
Nature Biotechnology 40 (6), 932-937, 2022
2872022
Learning latent permutations with gumbel-sinkhorn networks
G Mena, D Belanger, S Linderman, J Snoek
arXiv preprint arXiv:1802.08665, 2018
2842018
Structured prediction energy networks
D Belanger, A McCallum
International Conference on Machine Learning, 983-992, 2016
2592016
Earthquake ruptures with strongly rate-weakening friction and off-fault plasticity, part 2: Nonplanar faults
EM Dunham, D Belanger, L Cong, JE Kozdon
Bulletin of the Seismological Society of America 101 (5), 2308-2322, 2011
2582011
Earthquake ruptures with strongly rate-weakening friction and off-fault plasticity, Part 1: Planar faults
EM Dunham, D Belanger, L Cong, JE Kozdon
Bulletin of the Seismological Society of America 101 (5), 2296-2307, 2011
1962011
Synthesizing normalized faces from facial identity features
F Cole, D Belanger, D Krishnan, A Sarna, I Mosseri, WT Freeman
Proceedings of the IEEE conference on computer vision and pattern …, 2017
1862017
Rapid prediction of electron–ionization mass spectrometry using neural networks
JN Wei, D Belanger, RP Adams, D Sculley
ACS central science 5 (4), 700-708, 2019
1552019
End-to-end learning for structured prediction energy networks
D Belanger, B Yang, A McCallum
International Conference on Machine Learning, 429-439, 2017
1482017
Model-based reinforcement learning for biological sequence design
C Angermueller, D Dohan, D Belanger, R Deshpande, K Murphy, ...
International conference on learning representations, 2019
1422019
Boundless: Generative adversarial networks for image extension
P Teterwak, A Sarna, D Krishnan, A Maschinot, D Belanger, C Liu, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
1182019
Multilingual relation extraction using compositional universal schema
P Verga, D Belanger, E Strubell, B Roth, A McCallum
arXiv preprint arXiv:1511.06396, 2015
1172015
ProteInfer, deep neural networks for protein functional inference
T Sanderson, ML Bileschi, D Belanger, LJ Colwell
Elife 12, e80942, 2023
1062023
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
972020
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
612020
Is transfer learning necessary for protein landscape prediction?
A Shanehsazzadeh, D Belanger, D Dohan
arXiv preprint arXiv:2011.03443, 2020
582020
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