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Christopher Shallue
Christopher Shallue
Center for Astrophysics | Harvard & Smithsonian
Verified email at cfa.harvard.edu
Title
Cited by
Cited by
Year
Identifying exoplanets with deep learning: A five-planet resonant chain around kepler-80 and an eighth planet around kepler-90
CJ Shallue, A Vanderburg
The Astronomical Journal 155 (2), 94, 2018
2712018
Measuring the effects of data parallelism on neural network training
CJ Shallue, J Lee, J Antognini, J Sohl-Dickstein, R Frostig, GE Dahl
Journal of Machine Learning Research 20 (112), 1-49, 2018
2382018
On empirical comparisons of optimizers for deep learning
D Choi, CJ Shallue, Z Nado, J Lee, CJ Maddison, GE Dahl
arXiv preprint arXiv:1910.05446, 2019
1402019
Embedding text in hyperbolic spaces
B Dhingra, CJ Shallue, M Norouzi, AM Dai, GE Dahl
Twelfth Workshop on Graph-Based Methods for Natural Language Processing, 59-69, 2018
1002018
Which algorithmic choices matter at which batch sizes? insights from a noisy quadratic model
G Zhang, L Li, Z Nado, J Martens, S Sachdeva, G Dahl, C Shallue, ...
Advances in neural information processing systems 32, 2019
592019
Identifying exoplanets with deep learning. ii. two new super-earths uncovered by a neural network in k2 data
A Dattilo, A Vanderburg, CJ Shallue, AW Mayo, P Berlind, A Bieryla, ...
The Astronomical Journal 157 (5), 169, 2019
422019
Identifying exoplanets with deep learning. III. Automated triage and vetting of TESS candidates
L Yu, A Vanderburg, C Huang, CJ Shallue, IJM Crossfield, BS Gaudi, ...
The Astronomical Journal 158 (1), 25, 2019
322019
Permutation polynomials and orthomorphism polynomials of degree six
CJ Shallue, IM Wanless
Finite Fields and Their Applications 20, 84-92, 2013
272013
Faster neural network training with data echoing
D Choi, A Passos, CJ Shallue, GE Dahl
arXiv preprint arXiv:1907.05550, 2019
212019
A large batch optimizer reality check: Traditional, generic optimizers suffice across batch sizes
Z Nado, JM Gilmer, CJ Shallue, R Anil, GE Dahl
arXiv preprint arXiv:2102.06356, 2021
162021
Permutation polynomials of finite fields
CJ Shallue
arXiv preprint arXiv:1211.6044, 2012
92012
Identifying Exoplanets with Deep Learning. IV. Removing Stellar Activity Signals from Radial Velocity Measurements Using Neural Networks
ZL de Beurs, A Vanderburg, CJ Shallue, X Dumusque, AC Cameron, ...
arXiv preprint arXiv:2011.00003, 2020
22020
The EXPRES Stellar Signals Project II. State of the Field in Disentangling Photospheric Velocities
LL Zhao, DA Fischer, EB Ford, A Wise, M Cretignier, S Aigrain, ...
arXiv preprint arXiv:2201.10639, 2022
12022
A Machine Learning Inspired Method Reveals the Mass of K2-167 b
ZL de Beurs, A Vanderburg, CJ Shallue, JE Rodriguez, S Zieba, A Mortier, ...
Posters from the TESS Science Conference II (TSC2, 134, 2021
2021
Removing Stellar Activity Signals from Radial Velocity Measurements Using Neural Networks
Z de Beurs, A Vanderburg, CJ Shallue, Harps-N Collaboration
Bulletin of the American Astronomical Society 53 (3), 1019, 2021
2021
Identifying Exoplanets with Deep Learning: Removing Stellar Activity Signals from Radial Velocities Using Neural Networks
ZL de Beurs, A Vanderburg, CJ Shallue
Bulletin of the American Physical Society, 2021
2021
Systems and Methods for Reducing Idleness in a Machine-Learning Training System Using Data Echoing
D Choi, AT Passos, CJ Shallue, GE Dahl
US Patent App. 16/871,527, 2020
2020
Removing Stellar Activity from RVs Using Artificial Intelligence
ZL de Beurs, A Vanderburg, CJ Shallue, ...
American Astronomical Society Meeting Abstracts# 236 236, 107.07, 2020
2020
Identifying Exoplanets with Deep Learning: New Discoveries and Progress towards Planet Occurrence Rates in Kepler, K2, and TESS
A Vanderburg, CJ Shallue, A Dattilo, L Yu
AAS/Division for Extreme Solar Systems Abstracts 51, 103.03, 2019
2019
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