Avanti Shrikumar

发表

Learning Important Features Through Propagating Activation Differences pdf

Avanti Shrikumar, Anshul Kundaje, Peyton Greenside, 2017, ICML.

Not Just a Black Box: Learning Important Features Through Propagating Activation Differences pdf

Anna Shcherbina, Avanti Shrikumar, Anshul Kundaje, 2016, ArXiv.

Deep learning at base-resolution reveals motif syntax of the cis-regulatory code

Charles E. McAnany, A. Kundaje, J. Zeitlinger, 2019, bioRxiv.

Opportunities and obstacles for deep learning in biology and medicine [update in progress]

Anne E Carpenter, Srinivas C. Turaga, Brett K. Beaulieu-Jones, 2020 .

Not Just A Black Box : Interpretable Deep Learning by Propagating Activation Differences

Avanti Shrikumar, A. Shcherbina, 2016 .

Dynamic and Coordinated Epigenetic Regulation of Developmental Transitions in the Cardiac Lineage

Alexander R. Pico, Genevieve D. Erwin, K. Pollard, 2012, Cell.

Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation

Avanti Shrikumar, Anshul Kundaje, Amr Alexandari, 2020, ICML.

Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays

Avanti Shrikumar, Anshul Kundaje, Peyton Greenside, 2018, bioRxiv.

Opportunities and obstacles for deep learning in biology and medicine

Anne E Carpenter, Srinivas C. Turaga, Brett K. Beaulieu-Jones, 2017, bioRxiv.

Opportunities and obstacles for deep learning in biology and medicine: 2019 update

Anne E Carpenter, Srinivas C. Turaga, Brett K. Beaulieu-Jones, 2019 .

Deep learning at base-resolution reveals cis-regulatory motif syntax

Charles E. McAnany, A. Kundaje, J. Zeitlinger, 2020 .

A Flexible and Adaptive Framework for Abstention Under Class Imbalance

A. Kundaje, Avanti Shrikumar, Amr M. Alexandari, 2018 .

A General Framework for Abstention Under Label Shift

A. Kundaje, Avanti Shrikumar, Amr M. Alexandari, 2018, 1802.07024.

A General Framework for Abstention Under Label Shift

A. Kundaje, Avanti Shrikumar, Amr M. Alexandari, 2018, 1802.07024.

Towards More Realistic Simulated Datasets for Benchmarking Deep Learning Models in Regulatory Genomics

A. Kundaje, Avanti Shrikumar, Eva Prakash, 2021, bioRxiv.

fastISM: Performant in-silico saturation mutagenesis for convolutional neural networks

Avanti Shrikumar, Anshul Kundaje, Surag Nair, 2020, bioRxiv.

Domain-adaptive neural networks improve cross-species prediction of transcription factor binding

Avanti Shrikumar, Anshul Kundaje, Shaun Mahony, 2021, bioRxiv.

GkmExplain: fast and accurate interpretation of nonlinear gapped k-mer SVMs

Avanti Shrikumar, Anshul Kundaje, Eva Prakash, 2019, Bioinform..

Technical Note on Transcription Factor Motif Discovery from Importance Scores (TF-MoDISco) version 0.5.6.5

Avanti Shrikumar, Abhimanyu Banerjee, Anshul Kundaje, 2018, 1811.00416.

Base-resolution models of transcription factor binding reveal soft motif syntax

Avanti Shrikumar, Anshul Kundaje, Julien Gagneur, 2019, Nature Genetics.

The Kipoi repository accelerates community exchange and reuse of predictive models for genomics

Jun Cheng, Oliver Stegle, Roman Kreuzhuber, 2019, Nature Biotechnology.

Fourier-transform-based attribution priors improve the interpretability and stability of deep learning models for genomics

Avanti Shrikumar, Anshul Kundaje, Alex M. Tseng, 2020, bioRxiv.

Transcriptional reversion of cardiac myocyte fate during mammalian cardiac regeneration.

Gregory M. Fomovsky, Richard T. Lee, Vincent L. Butty, 2014, Circulation research.

Reverse-complement parameter sharing improves deep learning models for genomics

Avanti Shrikumar, Anshul Kundaje, Peyton Greenside, 2017, bioRxiv.

Kipoi: accelerating the community exchange and reuse of predictive models for genomics

Jun Cheng, Oliver Stegle, Ziga Avsec, 2018, bioRxiv.

Look at the Loss: Towards Robust Detection of False Positive Feature Interactions Learned by Neural Networks on Genomic Data

A. Kundaje, Avanti Shrikumar, Mara Finkelstein, 2020 .

Short tandem repeats recruit transcription factors to tune eukaryotic gene expression

A. Kundaje, J. Zeitlinger, R. Gordân, 2022, Biophysical Journal.

Towards a Better Understanding of Reverse-Complement Equivariance for Deep Learning Models in Genomics

A. Kundaje, Avanti Shrikumar, Hannah Zhou, 2021, MLBC.

Computationally Efficient Measures of Internal Neuron Importance pdf

Avanti Shrikumar, Anshul Kundaje, Jocelin Su, 2018, ArXiv.

De novo distillation of thermodynamic affinity from deep learning regulatory sequence models of in vivo protein-DNA binding

A. Kundaje, J. Zeitlinger, Avanti Shrikumar, 2023, bioRxiv.

EM with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation

Avanti Shrikumar, Anshul Kundaje, Amr Alexandari, 2019 .

Calibration with Bias-Corrected Temperature Scaling Improves Domain Adaptation Under Label Shift in Modern Neural Networks pdf

Avanti Shrikumar, Anshul Kundaje, A. Kundaje, 2019, ArXiv.

Selective Classification via Curve Optimization

Anshul Kundaje, Avanti Shrikumar, Amr Alexandari, 2018 .

Learning to Abstain via Curve Optimization pdf

Avanti Shrikumar, Anshul Kundaje, Amr Alexandari, 2018, ArXiv.

Gkmexplain: Fast and Accurate Interpretation of Nonlinear Gapped k-mer SVMs Using Integrated Gradients

Avanti Shrikumar, Anshul Kundaje, Eva Prakash, 2018, bioRxiv.

Short tandem repeats bind transcription factors to tune eukaryotic gene expression

A. Kundaje, J. Zeitlinger, R. Gordân, 2022, bioRxiv.

Dynamic and Coordinated Epigenetic Regulation of Developmental Transitions in the Cardiac Lineage

Alexander R. Pico, Genevieve D. Erwin, K. Pollard, 2012, Cell.

TF-MoDISco v0.4.4.2-alpha: Technical Note pdf

Anna Shcherbina, Avanti Shrikumar, Abhimanyu Banerjee, 2018, ArXiv.

Technical Note on Transcription Factor Motif Discovery from Importance Scores (TF-MoDISco) version 0.5.6.5

A. Kundaje, Avanti Shrikumar, A. Shcherbina, 2018, 1811.00416.