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ORCIDNathan Wycoff
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2020 – today
- 2024
[j6]Nathan Wycoff
, Lisa Singh, Ali Arab, Katharine M. Donato, Helge Marahrens:
The digital trail of Ukraine's 2022 refugee exodus. J. Comput. Soc. Sci. 7(2): 2147-2193 (2024)- [c5]Nathan Wycoff:
Surrogate Active Subspaces for Jump-Discontinuous Functions. AISTATS 2024: 4618-4626 - [i9]Nathan Wycoff, John W. Smith, Annie S. Booth, Robert B. Gramacy:
Voronoi Candidates for Bayesian Optimization. CoRR abs/2402.04922 (2024) - [i8]Nathan Wycoff:
Regression Trees Know Calculus. CoRR abs/2405.13846 (2024) - 2023
- [i7]Nathan Wycoff:
Surrogate Active Subspaces for Jump-Discontinuous Functions. CoRR abs/2310.10907 (2023) - 2022
- [j5]Nathan Wycoff, Mickaël Binois, Robert B. Gramacy:
Sensitivity Prewarping for Local Surrogate Modeling. Technometrics 64(4): 535-547 (2022) - [j4]Mickaël Binois, Nathan Wycoff:
A Survey on High-dimensional Gaussian Process Modeling with Application to Bayesian Optimization. ACM Trans. Evol. Learn. Optim. 2(2): 8:1-8:26 (2022) - [c4]Robert B. Gramacy, Annie Sauer, Nathan Wycoff:
Triangulation candidates for Bayesian optimization. NeurIPS 2022 - 2021
- [b1]Nathan Wycoff:
Gradient-Based Sensitivity Analysis with Kernels. Virginia Tech, Blacksburg, VA, USA, 2021 - [j3]Nathan Wycoff, Mickaël Binois, Stefan M. Wild:
Sequential Learning of Active Subspaces. J. Comput. Graph. Stat. 30(4): 1224-1237 (2021) - [c3]Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia:
Neko: a Library for Exploring Neuromorphic Learning Rules. ICONS 2021: 9:1-9:5 - [i6]Nathan Wycoff, Mickaël Binois, Robert B. Gramacy:
Sensitivity Prewarping for Local Surrogate Modeling. CoRR abs/2101.06296 (2021) - [i5]Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia:
Neko: a Library for Exploring Neuromorphic Learning Rules. CoRR abs/2105.00324 (2021) - [i4]Robert B. Gramacy, Annie Sauer, Nathan Wycoff:
Triangulation candidates for Bayesian optimization. CoRR abs/2112.07457 (2021) - 2020
- [i3]Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia:
Towards On-Chip Bayesian Neuromorphic Learning. CoRR abs/2005.04165 (2020)
2010 – 2019
- 2019
- [j2]Michelle Dowling, Nathan Wycoff, Brian Mayer, John E. Wenskovitch, Scotland Leman, Leanna House, Nicholas F. Polys, Chris North, Peter Hauck:
Interactive Visual Analytics for Sensemaking with Big Text. Big Data Res. 16: 49-58 (2019) - [c2]Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia:
Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout. ICONS 2019: 9:1-9:4 - [i2]Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia:
Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout. CoRR abs/1904.12904 (2019) - [i1]Nathan Wycoff, Mickaël Binois, Stefan M. Wild:
Sequential Learning of Active Subspaces. CoRR abs/1907.11572 (2019) - 2018
- [j1]Xin Chen, Jessica Zeitz Self, Leanna House, John E. Wenskovitch, Maoyuan Sun, Nathan Wycoff, Jane Robertson Evia, Scotland Leman, Chris North:
Be the Data: Embodied Visual Analytics. IEEE Trans. Learn. Technol. 11(1): 81-95 (2018) - 2015
- [c1]Lauren Bradel, Nathan Wycoff, Leanna House, Chris North:
Big Text Visual Analytics in Sensemaking. BDVA 2015: 9-16
Coauthor Index
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