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Geoffrey Roeder
Geoffrey Roeder
Подтвержден адрес электронной почты в домене princeton.edu - Главная страница
Название
Процитировано
Процитировано
Год
Backpropagation through the void: Optimizing control variates for black-box gradient estimation
W Grathwohl, D Choi, Y Wu, G Roeder, D Duvenaud
arXiv preprint arXiv:1711.00123, 2017
2242017
Sticking the landing: Simple, lower-variance gradient estimators for variational inference
G Roeder, Y Wu, DK Duvenaud
Advances in Neural Information Processing Systems 30, 2017
1352017
On linear identifiability of learned representations
G Roeder, L Metz, D Kingma
International Conference on Machine Learning, 9030-9039, 2021
242021
A data-driven computational scheme for the nonlinear mechanical properties of cellular mechanical metamaterials under large deformation
T Xue, A Beatson, M Chiaramonte, G Roeder, JT Ash, Y Menguc, ...
Soft matter 16 (32), 7524-7534, 2020
162020
Efficient amortised bayesian inference for hierarchical and nonlinear dynamical systems
G Roeder, T Meeds, P Grant, A Phillips, N Dalchau
International Conference on Machine Learning, 4445-4455, 2019
132019
Learning composable energy surrogates for PDE order reduction
A Beatson, J Ash, G Roeder, T Xue, RP Adams
Advances in neural information processing systems 33, 338-348, 2020
112020
Probabilistic graphical models and tensor networks: A hybrid framework
J Miller, G Roeder, TD Bradley
arXiv preprint arXiv:2106.15666, 2021
22021
Modelling ordinary differential equations using a variational auto encoder
E Meeds, G Roeder, N Dalchau
US Patent 11,030,275, 2021
12021
Quantum Machine Learning with Quantum-Probabilistic Generative Models
A Martinez, G Roeder, G Verdon-Akzam
Bulletin of the American Physical Society 66, 2021
2021
Design Motifs for Probabilistic Generative Design
G Roeder, N Killoran, W Grathwohl, D Duvenaud
2018
Learning Composable Energy Surrogates for PDE Order Reduction Open Website
A Beatson, JT Ash, G Roeder, T Xue, RP Adams
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Статьи 1–11