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ORCIDJuston Moore
Person information
- affiliation: Los Alamos National Laboratory, USA
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2020 – today
- 2023
[c9]Brian Wesley Bell, Michael Geyer, David Glickenstein, Amanda S. Fernandez, Juston Moore:
An Exact Kernel Equivalence for Finite Classification Models. TAG-ML 2023: 206-217- [i5]Kilian Zepf, Selma Wanna
, Marco Miani, Juston Moore, Jes Frellsen, Søren Hauberg, Aasa Feragen, Frederik Warburg:
Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty. CoRR abs/2303.13123 (2023) - [i4]Brian Bell, Michael Geyer, David Glickenstein, Amanda S. Fernandez, Juston Moore:
An Exact Kernel Equivalence for Finite Classification Models. CoRR abs/2308.00824 (2023) - [i3]Sayanton V. Dibbo, Juston S. Moore, Garrett T. Kenyon, Michael A. Teti:
LCANets++: Robust Audio Classification using Multi-layer Neural Networks with Lateral Competition. CoRR abs/2308.12882 (2023) - 2022
- [c8]Michael A. Teti, Garrett T. Kenyon, Ben Migliori, Juston Moore:
LCANets: Lateral Competition Improves Robustness Against Corruption and Attack. ICML 2022: 21232-21252 - [c7]Natalie Maus, Haydn Jones, Juston Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner:
Local Latent Space Bayesian Optimization over Structured Inputs. NeurIPS 2022 - [c6]Haydn T. Jones, Jacob M. Springer, Garrett T. Kenyon, Juston S. Moore:
If you've trained one you've trained them all: inter-architecture similarity increases with robustness. UAI 2022: 928-937 - [i2]Natalie Maus, Haydn T. Jones, Juston S. Moore, Matt J. Kusner, John Bradshaw, Jacob R. Gardner:
Local Latent Space Bayesian Optimization over Structured Inputs. CoRR abs/2201.11872 (2022) - 2020
- [c5]Nga T. T. Nguyen, Juston S. Moore, Garrett T. Kenyon:
Using models of cortical development based on sparse coding to discriminate between real and synthetically-generated faces. AIPR 2020: 1-7 - [c4]Maksim Ekin Eren, Juston S. Moore, Boian S. Alexandrov:
Multi-Dimensional Anomalous Entity Detection via Poisson Tensor Factorization. ISI 2020: 1-6
2010 – 2019
- 2018
- [c3]Elisabeth Baseman, Nathan DeBardeleben, Sean Blanchard, Juston S. Moore, Olena Tkachenko, Kurt B. Ferreira, Taniya Siddiqua, Vilas Sridharan:
Physics-Informed Machine Learning for DRAM Error Modeling. DFT 2018: 1-6 - 2016
- [c2]Melissa J. Turcotte, Juston S. Moore, Nick Heard, Aaron McPhall:
Poisson factorization for peer-based anomaly detection. ISI 2016: 208-210 - 2013
- [i1]Aaron Schein, Juston Moore, Hanna M. Wallach:
Inferring Multilateral Relations from Dynamic Pairwise Interactions. CoRR abs/1311.3982 (2013) - 2012
- [c1]Peter M. Krafft, Juston Moore, Bruce A. Desmarais, Hanna M. Wallach:
Topic-Partitioned Multinetwork Embeddings. NIPS 2012: 2816-2824
Coauthor Index
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last updated on 2023-12-04 22:55 CET by the dblp team
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