Jascha Sohl-Dickstein
Jascha Sohl-Dickstein
Google Brain
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Title
Cited by
Cited by
Year
Density estimation using Real NVP
L Dinh, J Sohl-Dickstein, S Bengio
International Conference on Learning Representations, 2016
8182016
Stratigraphy and sedimentology of a dry to wet eolian depositional system, Burns formation, Meridiani Planum, Mars
JP Grotzinger, RE Arvidson, JF Bell Iii, W Calvin, BC Clark, DA Fike, ...
Earth and Planetary Science Letters 240 (1), 11-72, 2005
4912005
Deep knowledge tracing
C Piech, J Bassen, J Huang, S Ganguli, M Sahami, LJ Guibas, ...
Advances in neural information processing systems, 505-513, 2015
3542015
Unrolled generative adversarial networks
L Metz, B Poole, D Pfau, J Sohl-Dickstein
International Conference on Learning Representations, 2016
3382016
On the expressive power of deep neural networks
M Raghu, B Poole, J Kleinberg, S Ganguli, J Sohl-Dickstein
International Conference on Machine Learning, 2017
3312017
Mars exploration rover Athena panoramic camera (Pancam) investigation
JF Bell III, SW Squyres, KE Herkenhoff, JN Maki, HM Arneson, D Brown, ...
Journal of Geophysical Research: Planets 108 (E12), 2003
3062003
Deep neural networks as gaussian processes
J Lee, Y Bahri, R Novak, SS Schoenholz, J Pennington, J Sohl-Dickstein
International Conference on Learning Representations, 2017
2802017
Exponential expressivity in deep neural networks through transient chaos
B Poole, S Lahiri, M Raghu, J Sohl-Dickstein, S Ganguli
Advances In Neural Information Processing Systems, 3360-3368, 2016
2642016
Rebar: Low-variance, unbiased gradient estimates for discrete latent variable models
G Tucker, A Mnih, CJ Maddison, J Lawson, J Sohl-Dickstein
Advances in Neural Information Processing Systems, oral track, 2627-2636, 2017
1702017
Svcca: Singular vector canonical correlation analysis for deep learning dynamics and interpretability
M Raghu, J Gilmer, J Yosinski, J Sohl-Dickstein
Advances in Neural Information Processing Systems, 6076-6085, 2017
1692017
Wide neural networks of any depth evolve as linear models under gradient descent
J Lee, L Xiao, S Schoenholz, Y Bahri, R Novak, J Sohl-Dickstein, ...
Advances in neural information processing systems, 8572-8583, 2019
1672019
Pancam multispectral imaging results from the Spirit rover at Gusev Crater
JF Bell, SW Squyres, RE Arvidson, HM Arneson, D Bass, D Blaney, ...
Science 305 (5685), 800-806, 2004
1612004
Sensitivity and generalization in neural networks: an empirical study
R Novak, Y Bahri, DA Abolafia, J Pennington, J Sohl-Dickstein
International Conference on Learning Representations, 2018
1602018
Deep information propagation
SS Schoenholz, J Gilmer, S Ganguli, J Sohl-Dickstein
International Conference on Learning Representations, 2016
1552016
New method for parameter estimation in probabilistic models: minimum probability flow
J Sohl-Dickstein, PB Battaglino, MR DeWeese
Physical review letters 107 (22), 220601, 2011
151*2011
Athena microscopic imager investigation
KE Herkenhoff, SW Squyres, JF Bell, JN Maki, HM Arneson, P Bertelsen, ...
Journal of Geophysical Research: Planets 108 (E12), 2003
1502003
Adversarial examples that fool both computer vision and time-limited humans
GF Elsayed, S Shankar, B Cheung, N Papernot, A Kurakin, I Goodfellow, ...
Neural Information Processing Systems, 2018
1492018
Pancam multispectral imaging results from the Opportunity Rover at Meridiani Planum
JF Bell, SW Squyres, RE Arvidson, HM Arneson, D Bass, W Calvin, ...
Science 306 (5702), 1703-1709, 2004
1352004
In‐flight calibration and performance of the Mars Exploration Rover Panoramic Camera (Pancam) instruments
JF Bell, J Joseph, JN Sohl‐Dickstein, HM Arneson, MJ Johnson, ...
Journal of Geophysical Research: Planets 111 (E2), 2006
1252006
Dynamical Isometry and a Mean Field Theory of CNNs: How to Train 10,000-Layer Vanilla Convolutional Neural Networks
L Xiao, Y Bahri, J Sohl-Dickstein, SS Schoenholz, J Pennington
International Conference on Machine Learning, 2018
1162018
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Articles 1–20