Articles with public access mandates - Andrew RossLearn more
Available somewhere: 14
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
Mandates: US National Science Foundation, US Department of Energy, Natural Sciences …
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
Mandates: US Department of Defense
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
Mandates: US National Institutes of Health
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
Mandates: US National Institutes of Health, UK Engineering and Physical Sciences …
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
Mandates: US National Science Foundation
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
Mandates: US National Institutes of Health
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
Mandates: US National Science Foundation
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
Mandates: US National Institutes of Health
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
Mandates: US National Institutes of Health
Benchmarks, algorithms, and metrics for hierarchical disentanglement
A Ross, F Doshi-Velez
International Conference on Machine Learning, 9084-9094, 2021
Mandates: US National Science Foundation
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
Mandates: US National Institutes of Health
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
Mandates: US National Science Foundation, US National Oceanic and Atmospheric …
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
Mandates: Swiss National Science Foundation, UK Engineering and Physical Sciences …
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
Mandates: Swiss National Science Foundation, US National Institutes of Health
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