Nathan Wycoff

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 18

Top Topics

Visual Analytics

Top Venues

ACM Trans. Evol. Learn. Optim.

Publications

Nathan Wycoff, John W. Smith, Annie S. Booth, Robert B. Gramacy
Voronoi Candidates for Bayesian Optimization. CoRR (2024)
Nathan Wycoff
Regression Trees Know Calculus. CoRR (2024)
Nathan Wycoff
Surrogate Active Subspaces for Jump-Discontinuous Functions. AISTATS (2024)
Nathan Wycoff
Surrogate Active Subspaces for Jump-Discontinuous Functions. CoRR (2023)
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
Sensitivity Prewarping for Local Surrogate Modeling. Technometrics 64 (4) (2022)
Mickaël Binois, Nathan Wycoff
A Survey on High-dimensional Gaussian Process Modeling with Application to Bayesian Optimization. ACM Trans. Evol. Learn. Optim. 2 (2) (2022)
Robert B. Gramacy, Annie Sauer, Nathan Wycoff
Triangulation candidates for Bayesian optimization. NeurIPS (2022)
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
Sensitivity Prewarping for Local Surrogate Modeling. CoRR (2021)
Nathan Wycoff, Mickaël Binois, Stefan M. Wild
Sequential Learning of Active Subspaces. J. Comput. Graph. Stat. 30 (4) (2021)
Robert B. Gramacy, Annie Sauer, Nathan Wycoff
Triangulation candidates for Bayesian optimization. CoRR (2021)
Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia
Neko: a Library for Exploring Neuromorphic Learning Rules. ICONS (2021)
Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia
Neko: a Library for Exploring Neuromorphic Learning Rules. CoRR (2021)
Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia
Towards On-Chip Bayesian Neuromorphic Learning. CoRR (2020)
Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia
Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout. CoRR (2019)
Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia
Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout. ICONS (2019)
Nathan Wycoff, Mickaël Binois, Stefan M. Wild
Sequential Learning of Active Subspaces. CoRR (2019)
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 (2019)
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) (2018)
Lauren Bradel, Nathan Wycoff, Leanna House, Chris North
Big Text Visual Analytics in Sensemaking. BDVA (2015)