Nathan Wycoff

28 papers A* 1A 1Journal 22Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Voronoi candidates for Bayesian optimization.
J. Glob. Optim.
Nathan Wycoff, John W. Smith, Annie S. Booth, Robert B. Gramacy
2025 J jnl
A Probabilistic Basis for Low-Rank Matrix Learning.
CoRR
Simon Segert, Nathan Wycoff
2025 J jnl
Active Subspaces in Infinite Dimension.
CoRR
Poorbita Kundu, Nathan Wycoff
2025 J jnl
Formal Bayesian Transfer Learning via the Total Risk Prior.
CoRR
Nathan Wycoff, Ali Arab, Lisa Singh
2025 J jnl
On Thompson Sampling and Bilateral Uncertainty in Additive Bayesian Optimization.
CoRR
Nathan Wycoff
2025 J jnl
Understanding the role of sentiment and emotion for predicting forced displacement.
EPJ Data Sci.
Helge Marahrens, Ameeta Agrawal, Ali Arab, Katharine M. Donato, Yaguang Liu, Nathan Wycoff, Mohamed Ahmed, Colin Hwang, Lina Laghzaoui, Kate Liggio, Bernardo Medeiros, Jenny Park, Rich Pihlstrom, Eliza Salamon, Mattea Whitlow, Lisa Singh
2024 J jnl
Proximal Iteration for Nonlinear Adaptive Lasso.
CoRR
Nathan Wycoff, Lisa Singh, Ali Arab, Katharine M. Donato
2024 J jnl
Regression Trees Know Calculus.
CoRR
Nathan Wycoff
2024 A conf
Surrogate Active Subspaces for Jump-Discontinuous Functions.
AISTATS
Nathan Wycoff
2024 J jnl
The digital trail of Ukraine's 2022 refugee exodus.
J. Comput. Soc. Sci.
Nathan Wycoff, Lisa Singh, Ali Arab, Katharine M. Donato, Helge Marahrens
2024 J jnl
Voronoi Candidates for Bayesian Optimization.
CoRR
Nathan Wycoff, John W. Smith, Annie S. Booth, Robert B. Gramacy
2023 J jnl
Surrogate Active Subspaces for Jump-Discontinuous Functions.
CoRR
Nathan Wycoff
2022 J jnl
A Survey on High-dimensional Gaussian Process Modeling with Application to Bayesian Optimization.
ACM Trans. Evol. Learn. Optim.
Mickaël Binois, Nathan Wycoff
2022 J jnl
Sensitivity Prewarping for Local Surrogate Modeling.
Technometrics
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
2022 A* conf
Triangulation candidates for Bayesian optimization.
NeurIPS
Robert B. Gramacy, Annie Sauer, Nathan Wycoff
2021 — —
Gradient-Based Sensitivity Analysis with Kernels.
Nathan Wycoff
2021 — conf
Neko: a Library for Exploring Neuromorphic Learning Rules.
ICONS
Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia
2021 J jnl
Neko: a Library for Exploring Neuromorphic Learning Rules.
CoRR
Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia
2021 J jnl
Sensitivity Prewarping for Local Surrogate Modeling.
CoRR
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
2021 J jnl
Sequential Learning of Active Subspaces.
J. Comput. Graph. Stat.
Nathan Wycoff, Mickaël Binois, Stefan M. Wild
2021 J jnl
Triangulation candidates for Bayesian optimization.
CoRR
Robert B. Gramacy, Annie Sauer, Nathan Wycoff
2020 J jnl
Towards On-Chip Bayesian Neuromorphic Learning.
CoRR
Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia
2019 J jnl
Interactive Visual Analytics for Sensemaking with Big Text.
Big Data Res.
Michelle Dowling, Nathan Wycoff, Brian Mayer, John E. Wenskovitch, Scotland Leman, Leanna House, Nicholas F. Polys, Chris North, Peter Hauck
2019 — conf
Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout.
ICONS
Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia
2019 J jnl
Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout.
CoRR
Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia
2019 J jnl
Sequential Learning of Active Subspaces.
CoRR
Nathan Wycoff, Mickaël Binois, Stefan M. Wild
2018 J jnl
Be the Data: Embodied Visual Analytics.
IEEE Trans. Learn. Technol.
Xin Chen, Jessica Zeitz Self, Leanna House, John E. Wenskovitch, Maoyuan Sun, Nathan Wycoff, Jane Robertson Evia, Scotland Leman, Chris North
2015 — conf
Big Text Visual Analytics in Sensemaking.
BDVA
Lauren Bradel, Nathan Wycoff, Leanna House, Chris North