Avanti Shrikumar
Avanti Shrikumar
Verified email at stanford.edu
Title
Cited by
Cited by
Year
Learning important features through propagating activation differences
A Shrikumar, P Greenside, A Kundaje
International Conference on Machine Learning, 3145-3153, 2017
15332017
Opportunities and obstacles for deep learning in biology and medicine
T Ching, DS Himmelstein, BK Beaulieu-Jones, AA Kalinin, BT Do, ...
Journal of The Royal Society Interface 15 (141), 20170387, 2018
10032018
Dynamic and coordinated epigenetic regulation of developmental transitions in the cardiac lineage
JA Wamstad, JM Alexander, RM Truty, A Shrikumar, F Li, KE Eilertson, ...
Cell 151 (1), 206-220, 2012
5582012
Not just a black box: Learning important features through propagating activation differences
A Shrikumar, P Greenside, A Shcherbina, A Kundaje
arXiv preprint arXiv:1605.01713, 2016
3322016
Transcriptional reversion of cardiac myocyte fate during mammalian cardiac regeneration
CC O’Meara, JA Wamstad, RA Gladstone, GM Fomovsky, VL Butty, ...
Circulation research 116 (5), 804-815, 2015
1202015
The Kipoi repository accelerates community exchange and reuse of predictive models for genomics
Ž Avsec, R Kreuzhuber, J Israeli, N Xu, J Cheng, A Shrikumar, A Banerjee, ...
Nature biotechnology 37 (6), 592-600, 2019
622019
Base-resolution models of transcription-factor binding reveal soft motif syntax
Ž Avsec, M Weilert, A Shrikumar, S Krueger, A Alexandari, K Dalal, ...
Nature Genetics 53 (3), 354-366, 2021
582021
Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays
R Movva, P Greenside, GK Marinov, S Nair, A Shrikumar, A Kundaje
PLoS One 14 (6), e0218073, 2019
392019
Reverse-complement parameter sharing improves deep learning models for genomics
A Shrikumar, P Greenside, A Kundaje
bioRxiv, 103663, 2017
312017
Kipoi: accelerating the community exchange and reuse of predictive models for genomics
Ž Avsec
ICML Workshop for Computational Biology, 2018
262018
Deep learning at base-resolution reveals motif syntax of the cis-regulatory code
Ž Avsec, M Weilert, A Shrikumar, A Alexandari, S Krueger, K Dalal, ...
BioRxiv, 737981, 2019
232019
GkmExplain: fast and accurate interpretation of nonlinear gapped k-mer SVMs
A Shrikumar, E Prakash, A Kundaje
Bioinformatics 35 (14), i173-i182, 2019
202019
Technical note on transcription factor motif discovery from importance scores (TF-MoDISco) version 0.5. 6.5
A Shrikumar, K Tian, Ž Avsec, A Shcherbina, A Banerjee, M Sharmin, ...
arXiv preprint arXiv:1811.00416, 2018
142018
Maximum likelihood with bias-corrected calibration is hard-to-beat at label shift adaptation
A Alexandari, A Kundaje, A Shrikumar
International Conference on Machine Learning, 222-232, 2020
122020
Tf-Modisco v0. 4.4. 2-Alpha
A Shrikumar, K Tian, A Shcherbina, Ž Avsec, A Banerjee, M Sharmin, ...
arXiv preprint arXiv:1811.00416, 2018
102018
Reverse-complement parameter sharing improves deep learning models for genomics. bioRxiv
A Shrikumar, P Greenside, A Kundaje
January, 2017
92017
Separable fully connected layers improve deep learning models for genomics
AM Alexandari, A Shrikumar, A Kundaje
bioRxiv, 146431, 2017
82017
Fourier-transform-based attribution priors improve the interpretability and stability of deep learning models for genomics
A Tseng, A Shrikumar, A Kundaje
Advances in Neural Information Processing Systems 33, 2020
72020
Calibration with bias-corrected temperature scaling improves domain adaptation under label shift in modern neural networks
A Shrikumar, A Kundaje
Preprint at https://arxiv. org/abs/1901.06852 v1, 2019
6*2019
Computationally efficient measures of internal neuron importance
A Shrikumar, J Su, A Kundaje
arXiv preprint arXiv:1807.09946, 2018
52018
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Articles 1–20