Geoff Pleiss
Geoff Pleiss
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On calibration of modern neural networks
C Guo, G Pleiss, Y Sun, KQ Weinberger
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
Snapshot ensembles: Train 1, get m for free
G Huang, Y Li, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger
arXiv preprint arXiv:1704.00109, 2017
On fairness and calibration
G Pleiss, M Raghavan, F Wu, J Kleinberg, KQ Weinberger
Advances in Neural Information Processing Systems, 5680-5689, 2017
Deep feature interpolation for image content changes
P Upchurch, J Gardner, G Pleiss, K Bala, R Pless, N Snavely, ...
arXiv preprint arXiv:1611.05507, 2016
Memory-efficient implementation of densenets
G Pleiss, D Chen, G Huang, T Li, L van der Maaten, KQ Weinberger
arXiv preprint arXiv:1707.06990, 2017
Gpytorch: Blackbox matrix-matrix gaussian process inference with gpu acceleration
J Gardner, G Pleiss, KQ Weinberger, D Bindel, AG Wilson
Advances in Neural Information Processing Systems, 7576-7586, 2018
Product kernel interpolation for scalable Gaussian processes
JR Gardner, G Pleiss, R Wu, KQ Weinberger, AG Wilson
arXiv preprint arXiv:1802.08903, 2018
Exact Gaussian processes on a million data points
K Wang, G Pleiss, J Gardner, S Tyree, KQ Weinberger, AG Wilson
Advances in Neural Information Processing Systems, 14622-14632, 2019
Constant-time predictive distributions for Gaussian processes
G Pleiss, JR Gardner, KQ Weinberger, AG Wilson
arXiv preprint arXiv:1803.06058, 2018
Pseudo-lidar++: Accurate depth for 3d object detection in autonomous driving
Y You, Y Wang, WL Chao, D Garg, G Pleiss, B Hariharan, M Campbell, ...
arXiv preprint arXiv:1906.06310, 2019
Convolutional Networks with Dense Connectivity
G Huang, Z Liu, G Pleiss, L Van Der Maaten, K Weinberger
IEEE transactions on pattern analysis and machine intelligence, 2019
Unsupervised machine learning for accelerating discoveries from temperature dependent X-ray data
J Venderley, M Matty, V Kishore, G Pleiss, K Weinberger, EA Kim
Bulletin of the American Physical Society, 2020
Deep Sigma Point Processes
M Jankowiak, G Pleiss, JR Gardner
arXiv preprint arXiv:2002.09112, 2020
Identifying Mislabeled Data using the Area Under the Margin Ranking
G Pleiss, T Zhang, ER Elenberg, KQ Weinberger
arXiv preprint arXiv:2001.10528, 2020
Sparse Gaussian Process Regression Beyond Variational Inference
M Jankowiak, G Pleiss, JR Gardner
arXiv preprint arXiv:1910.07123, 2019
Potential Predictability of Regional Precipitation and Discharge Extremes Using Synoptic-Scale Climate Information via Machine Learning: An Evaluation for the Eastern …
J Knighton, G Pleiss, E Carter, S Lyon, MT Walter, S Steinschneider
Journal of Hydrometeorology 20 (5), 883-900, 2019
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