Mark Goldstein
Mark Goldstein
Courant Institute, NYU
Verified email at - Homepage
Cited by
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Practical whole-system provenance capture
T Pasquier, X Han, M Goldstein, T Moyer, D Eyers, M Seltzer, J Bacon
Proceedings of the 2017 Symposium on Cloud Computing, 405-418, 2017
Understanding failures in out-of-distribution detection with deep generative models
L Zhang, M Goldstein, R Ranganath
International Conference on Machine Learning, 12427-12436, 2021
{FRAPpuccino}: Fault-detection through Runtime Analysis of Provenance
X Han, T Pasquier, T Ranjan, M Goldstein, M Seltzer
9th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 17), 2017
X-CAL: Explicit Calibration for Survival Analysis
M Goldstein, X Han, A Puli, AJ Perotte, R Ranganath
Advances in Neural Information Processing Systems 2020 33, 2020
SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers
N Ma, M Goldstein, MS Albergo, NM Boffi, E Vanden-Eijnden, S Xie
arXiv preprint arXiv:2401.08740, 2024
Where to diffuse, how to diffuse, and how to get back: Automated learning for multivariate diffusions
R Singhal, M Goldstein, R Ranganath
arXiv preprint arXiv:2302.07261, 2023
Inverse-weighted survival games
X Han, M Goldstein, A Puli, T Wies, A Perotte, R Ranganath
Advances in neural information processing systems 34, 2160-2172, 2021
Stochastic interpolants with data-dependent couplings
MS Albergo, M Goldstein, NM Boffi, R Ranganath, E Vanden-Eijnden
arXiv preprint arXiv:2310.03725, 2023
Learning invariant representations with missing data
M Goldstein, JH Jacobsen, O Chau, A Saporta, AM Puli, R Ranganath, ...
Conference on Causal Learning and Reasoning, 290-301, 2022
Survival mixture density networks
X Han, M Goldstein, R Ranganath
Machine Learning for Healthcare Conference, 224-248, 2022
QTNet: Predicting Drug-Induced QT Prolongation With Artificial Intelligence–Enabled Electrocardiograms
H Zhang, C Tarabanis, N Jethani, M Goldstein, S Smith, L Chinitz, ...
Clinical Electrophysiology 10 (5), 956-966, 2024
Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning
Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, SD Maidman, ...
European Heart Journal: Acute Cardiovascular Care, zuae037, 2024
Probabilistic Forecasting with Stochastic Interpolants and F\" ollmer Processes
Y Chen, M Goldstein, M Hua, MS Albergo, NM Boffi, E Vanden-Eijnden
arXiv preprint arXiv:2403.13724, 2024
A dynamic risk score for early prediction of cardiogenic shock using machine learning
Y Hu, A Lui, M Goldstein, M Sudarshan, A Tinsay, C Tsui, S Maidman, ...
arXiv preprint arXiv:2303.12888, 2023
GATO: Gates Are Not the Only Option
M Goldstein, X Han, R Ranganath
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