Anshul Kundaje

Orcid: 0000-0003-3084-2287

According to our database1, Anshul Kundaje authored at least 35 papers between 2004 and 2023.

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Bibliography

2023
GENCODE: reference annotation for the human and mouse genomes in 2023.
Nucleic Acids Res., January, 2023

Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design.
CoRR, 2022

Accelerating <i>in silico</i> saturation mutagenesis using compressed sensing.
Bioinform., 2022

2021
Towards a Better Understanding of Reverse-Complement Equivariance for Deep Learning Models in Genomics.
Proceedings of the Machine Learning in Computational Biology Meeting, 2021

Towards More Realistic Simulated Datasets for Benchmarking Deep Learning Models in Regulatory Genomics.
Proceedings of the Machine Learning in Computational Biology Meeting, 2021


2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts.
CoRR, 2020

Fourier-transform-based attribution priors improve the interpretability and stability of deep learning models for genomics.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift Adaptation.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Calibration with Bias-Corrected Temperature Scaling Improves Domain Adaptation Under Label Shift in Modern Neural Networks.
CoRR, 2019

GkmExplain: fast and accurate interpretation of nonlinear gapped k-mer SVMs.
Bioinform., 2019

Integrating regulatory DNA sequence and gene expression to predict genome-wide chromatin accessibility across cellular contexts.
Bioinform., 2019

2018
TF-MoDISco v0.4.4.2-alpha: Technical Note.
CoRR, 2018

Computationally Efficient Measures of Internal Neuron Importance.
CoRR, 2018

Learning to Abstain via Curve Optimization.
CoRR, 2018

GenomeDISCO: a concordance score for chromosome conformation capture experiments using random walks on contact map graphs.
Bioinform., 2018

Discovering epistatic feature interactions from neural network models of regulatory DNA sequences.
Bioinform., 2018

Prediction of protein-ligand interactions from paired protein sequence motifs and ligand substructures.
Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018

2017
Vicus: Exploiting local structures to improve network-based analysis of biological data.
PLoS Comput. Biol., 2017

Denoising genome-wide histone ChIP-seq with convolutional neural networks.
Bioinform., 2017

Learning Important Features Through Propagating Activation Differences.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences.
CoRR, 2016

Unsupervised Learning from Noisy Networks with Applications to Hi-C Data.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Integrative analysis of 111 reference human epigenomes Open.
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Nat., 2015

2014
Comparative analysis of metazoan chromatin organization Open.
Nat., 2014

Comparative analysis of regulatory information and circuits across distant species Open.
Nat., 2014

2013
Clustering reveals ubiquitous heterogeneity and asymmetry of genomic signals at functional elements.
Tiny Trans. Comput. Sci., 2013

2008
A Predictive Model of the Oxygen and Heme Regulatory Network in Yeast.
PLoS Comput. Biol., 2008

2006
A classification-based framework for predicting and analyzing gene regulatory response.
BMC Bioinform., 2006

2005
Combining Sequence and Time Series Expression Data to Learn Transcriptional Modules.
IEEE ACM Trans. Comput. Biol. Bioinform., 2005

Motif Discovery Through Predictive Modeling of Gene Regulation.
Proceedings of the Research in Computational Molecular Biology, 2005

2004
Spectrogram Analysis of Genomes.
EURASIP J. Adv. Signal Process., 2004

Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response.
Proceedings of the Regulatory Genomics, 2004

Predicting genetic regulatory response using classification.
Proceedings of the Proceedings Twelfth International Conference on Intelligent Systems for Molecular Biology/Third European Conference on Computational Biology 2004, 2004


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