Avanti Shrikumar
According to our database1,
Avanti Shrikumar
authored at least 13 papers
between 2016 and 2021.
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Bibliography
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
PhD thesis, 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
Bioinform., 2019
Suggested Best Practices for Interpreting Deep Learning Models via Input-Level Importance Scores.
Proceedings of the Symposium Interpretable AI for Well-being: Understanding Cognitive Bias and Social Embeddedness co-located with Association for the Advancement of Artificial Intelligence 2019 Spring Symposium (AAAI-Spring Symposium 2019), 2019
2018
2017
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