Jamie Smith

15 papers A* 2Journal 11Unranked 1
YearRankTypeTitle / Venue / Authors
2024 J jnl
Strongly cospectral vertices.
Australas. J Comb.
Chris D. Godsil, Jamie Smith
2024 — conf
Towards the Formal Verification of SysML v2 Models.
MoDELS (Companion)
Vince Molnár, Bence Graics, András Vörös, Stefano Tonetta, Luca Cristoforetti, Greg Kimberly, Pamela Dyer, Kristin Giammarco, Manfred Köthe, John Hester, Jamie Smith, Christoph Grimm
2023 A* conf
Score-Based Diffusion Models as Principled Priors for Inverse Imaging.
ICCV
Berthy T. Feng, Jamie Smith, Michael Rubinstein, Huiwen Chang, Katherine L. Bouman, William T. Freeman
2023 J jnl
Score-Based Diffusion Models as Principled Priors for Inverse Imaging.
CoRR
Berthy T. Feng, Jamie Smith, Michael Rubinstein, Huiwen Chang, Katherine L. Bouman, William T. Freeman
2022 J jnl
Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure.
Trans. Mach. Learn. Res.
Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic
2022 J jnl
Ensembles of Classifiers: a Bias-Variance Perspective.
Trans. Mach. Learn. Res.
Neha Gupta, Jamie Smith, Ben Adlam, Zelda E. Mariet
2022 J jnl
Ensembling over Classifiers: a Bias-Variance Perspective.
CoRR
Neha Gupta, Jamie Smith, Ben Adlam, Zelda Mariet
2022 J jnl
Understanding the bias-variance tradeoff of Bregman divergences.
CoRR
Ben Adlam, Neha Gupta, Zelda Mariet, Jamie Smith
2021 J jnl
Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems.
CoRR
Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic
2020 J jnl
Adoption of an Electronic Medical Record Tool for Childhood Obesity by Primary Care Providers.
Appl. Clin. Inform.
Amy Williams, Christy B. Turer, Jamie Smith, Isabelle Nievera, Laura McCulloch, Nuha Wareg, Megan Clary, Anuradha Rajagopalan, Ross C. Brownson, Richelle J. Koopman, Sarah Hampl
2020 J jnl
Critiquing Protein Family Classification Models Using Sufficient Input Subsets.
J. Comput. Biol.
Brandon Carter, Maxwell L. Bileschi, Jamie Smith, Theo Sanderson, Drew Bryant, David Belanger, Lucy J. Colwell
2017 A* conf
TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks.
KDD
Heng-Tze Cheng, Zakaria Haque, Lichan Hong, Mustafa Ispir, Clemens Mewald, Illia Polosukhin, Georgios Roumpos, D. Sculley, Jamie Smith, David Soergel, Yuan Tang, Philipp Tucker, Martin Wicke, Cassandra Xia, Jianwei Xie
2017 J jnl
TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks.
CoRR
Heng-Tze Cheng, Zakaria Haque, Lichan Hong, Mustafa Ispir, Clemens Mewald, Illia Polosukhin, Georgios Roumpos, D. Sculley, Jamie Smith, David Soergel, Yuan Tang, Philipp Tucker, Martin Wicke, Cassandra Xia, Jianwei Xie
2012 — ch.
Algorithms for Quantum Computers.
Handbook of Natural Computing
Jamie Smith, Michele Mosca
2011 J jnl
On the Limitations of Graph Invariants Inspired by Quantum Walks.
Electron. Notes Discret. Math.
Jamie Smith