Jesse Zhang
Jesse Zhang
Electrical Engineering PhD Student, Stanford University
Verified email at - Homepage
Cited by
Cited by
Generalizable adversarial training via spectral normalization
F Farnia, JM Zhang, D Tse
arXiv preprint arXiv:1811.07457, 2018
Fast and accurate single-cell RNA-seq analysis by clustering of transcript-compatibility counts
V Ntranos, GM Kamath, JM Zhang, L Pachter, DN Tse
Genome biology 17 (1), 112, 2016
Lysine-specific demethylase 1 has dual functions as a major regulator of androgen receptor transcriptional activity
C Cai, HH He, S Gao, S Chen, Z Yu, Y Gao, S Chen, MW Chen, J Zhang, ...
Cell reports 9 (5), 1618-1627, 2014
Valid post-clustering differential analysis for single-cell RNA-Seq
JM Zhang, GM Kamath, NT David
Cell systems 9 (4), 383-392. e6, 2019
An interpretable framework for clustering single-cell RNA-Seq datasets
JM Zhang, J Fan, HC Fan, D Rosenfeld, DN Tse
BMC bioinformatics 19 (1), 1-12, 2018
Porcupine neural networks:(almost) all local optima are global
S Feizi, H Javadi, J Zhang, D Tse
arXiv preprint arXiv:1710.02196, 2017
Prediction of price increase for magic: The gathering cards
M Pawlicki, J Polin, J Zhang
Recuperado de http://cs229. stanford. edu/proj2014/Matt% 20Pawlicki,% 20Joe …, 2014
A Fourier-based approach to generalization and optimization in deep learning
F Farnia, JM Zhang, NT David
IEEE Journal on Selected Areas in Information Theory 1 (1), 145-156, 2020
Porcupine neural networks: Approximating neural network landscapes
S Feizi, H Javadi, J Zhang, D Tse
Advances in Neural Information Processing Systems 31, 2018
Towards a Post-Clustering Test for Differential Expression.
JM Zhang, GM Kamath, NC David
RECOMB, 328-329, 2019
A spectral approach to generalization and optimization in neural networks
F Farnia, J Zhang, D Tse
Learning the language of the genome using RNNs
JM Zhang, GM Kamath
Go to reference in article, 2016
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