Tim G. J. Rudner

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 4 papers. Top paper: “A Study of Bayesian Neural Network Surrogates for Bayesian Optimization”.

A Study of Bayesian Neural Network Surrogates for Bayesian Optimization

arXiv (Cornell University)(2023)10.48550/arxiv.2305.20028

N/A

0DataRank · unranked

5 citations

Tim G. J. Rudner, Andrew Gordon Wilson, Yucen Lily Li

Function-Space Regularization in Neural Networks: A Probabilistic Perspective

arXiv (Cornell University)(2023)10.48550/arxiv.2312.17162

N/A

0DataRank · unranked

1 citations

Sanyam Kapoor, Shikai Qiu, Andrew Gordon Wilson, Tim G. J. Rudner

Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds

arXiv (Cornell University)(2024)10.48550/arxiv.2410.12779

N/A

0DataRank · unranked

4 citations

Danqi Liao, Kincaid Macdonald, Yanlei Zhang, Chen Liu, Guillaume Huguet +5 more

A Monte Carlo Framework for Calibrated Uncertainty Estimation in Sequence Prediction

arXiv (Cornell University)(2024)10.48550/arxiv.2410.23272

N/A

0DataRank · unranked

0 citations

Weicheng Zhu, Joseph Keslin, Laure Zanna, Tim G. J. Rudner, Carlos Fernandez‐Granda +1 more