Andrew Ross
Andrew Ross
PhD student, Harvard University
Verified email at - Homepage
Cited by
Cited by
Tackling Climate Change with Machine Learning
D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, ...
ACM Computing Surveys 55 (2), 1-96, 2019
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients
AS Ross, F Doshi-Velez
Thirty-Second AAAI Conference on Artificial Intelligence, 1660-1669, 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations
AS Ross, MC Hughes, Doshi-Velez, Finale
Proceedings of the Twenty-Sixth International Joint Conference on Artificial …, 2017
Human-in-the-loop interpretability prior
I Lage, A Ross, SJ Gershman, B Kim, F Doshi-Velez
Advances in neural information processing systems 31, 2018
Improving sepsis treatment strategies by combining deep and kernel-based reinforcement learning
X Peng, Y Ding, D Wihl, O Gottesman, M Komorowski, HL Li-wei, A Ross, ...
AMIA Annual Symposium Proceedings 2018, 887, 2018
Design Continuums and the Path Toward Self-Designing Key-Value Stores that Know and Learn.
S Idreos, N Dayan, W Qin, M Akmanalp, S Hilgard, A Ross, J Lennon, ...
CIDR, 2019
Evaluating the interpretability of generative models by interactive reconstruction
A Ross, N Chen, EZ Hang, EL Glassman, F Doshi-Velez
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021
Benchmarking of machine learning ocean subgrid parameterizations in an idealized model
A Ross, Z Li, P Perezhogin, C Fernandez‐Granda, L Zanna
Journal of Advances in Modeling Earth Systems 15 (1), 2023
Ensembles of locally independent prediction models
A Ross, W Pan, L Celi, F Doshi-Velez
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5527-5536, 2020
Hydrodynamic irreversibility in particle suspensions with nonuniform strain
JS Guasto, AS Ross, JP Gollub
Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 81 (6 …, 2010
The neural lasso: Local linear sparsity for interpretable explanations
A Ross, I Lage, F Doshi-Velez
Workshop on Transparent and Interpretable Machine Learning in Safety …, 2017
Benchmarks, algorithms, and metrics for hierarchical disentanglement
A Ross, F Doshi-Velez
International Conference on Machine Learning, 9084-9094, 2021
Assessment of a prediction model for antidepressant treatment stability using supervised topic models
MC Hughes, MF Pradier, AS Ross, TH McCoy, RH Perlis, F Doshi-Velez
JAMA network open 3 (5), e205308-e205308, 2020
GCM-filters: A Python package for diffusion-based spatial filtering of gridded data
N Loose, R Abernathey, I Grooms, J Busecke, A Guillaumin, E Yankovsky, ...
Journal of Open Source Software 7 (70), 2022
Learning qualitatively diverse and interpretable rules for classification
AS Ross, W Pan, F Doshi-Velez
arXiv preprint arXiv:1806.08716, 2018
Learning key-value store design
S Idreos, N Dayan, W Qin, M Akmanalp, S Hilgard, A Ross, J Lennon, ...
arXiv preprint arXiv:1907.05443, 2019
Improving counterfactual reasoning with kernelised dynamic mixing models
S Parbhoo, O Gottesman, AS Ross, M Komorowski, A Faisal, I Bon, ...
PloS one 13 (11), e0205839, 2018
Learning predictive and interpretable timeseries summaries from ICU data
N Johnson, S Parbhoo, AS Ross, F Doshi-Velez
AMIA Annual Symposium Proceedings 2021, 581, 2021
Refactoring Machine Learning
AS Ross, JZ Forde
NeurIPS 2018 Workshop on Critiquing and Correcting Trends in Machine Learning, 2018
Controlled Direct Effect Priors for Bayesian Neural Networks
J Du, AS Ross, Y Shavit, F Doshi-Velez
NeurIPS 2019 Workshop on Bayesian Deep Learning, 2019
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