Charlie Nash
Charlie Nash
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Relational inductive biases, deep learning, and graph networks
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
11632018
The shape variational autoencoder: A deep generative model of part‐segmented 3D objects
C Nash, CKI Williams
Computer Graphics Forum 36 (5), 1-12, 2017
722017
Efficient graph generation with graph recurrent attention networks
R Liao, Y Li, Y Song, S Wang, C Nash, WL Hamilton, D Duvenaud, ...
arXiv preprint arXiv:1910.00760, 2019
602019
Overcoming occlusion with inverse graphics
P Moreno, CKI Williams, C Nash, P Kohli
European Conference on Computer Vision, 170-185, 2016
262016
Polygen: An autoregressive generative model of 3d meshes
C Nash, Y Ganin, SMA Eslami, P Battaglia
International Conference on Machine Learning, 7220-7229, 2020
212020
Autoregressive energy machines
C Nash, C Durkan
International Conference on Machine Learning, 1735-1744, 2019
202019
The multi-entity variational autoencoder
C Nash, SMA Eslami, C Burgess, I Higgins, D Zoran, T Weber, P Battaglia
NIPS Workshops, 2017
152017
Inverting supervised representations with autoregressive neural density models
C Nash, N Kushman, CKI Williams
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
122019
Relational Inductive Biases
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
Deep Learning, and Graph Networks 2018, 1-38arXiv, 1806
121806
Relational inductive biases, deep learning, and graph networks. arXiv
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
Learning, 2018
102018
Autoencoders and probabilistic inference with missing data: An exact solution for the factor analysis case
CKI Williams, C Nash, A Nazábal
arXiv preprint arXiv:1801.03851, 2018
72018
Variable-rate discrete representation learning
S Dieleman, C Nash, J Engel, K Simonyan
arXiv preprint arXiv:2103.06089, 2021
12021
Generative Entity Networks: Disentangling Entitites and Attributes in Visual Scenes using Partial Natural Language Descriptions
C Nash, S Nowozin, N Kushman
12018
Generating Images with Sparse Representations
C Nash, J Menick, S Dieleman, PW Battaglia
arXiv preprint arXiv:2103.03841, 2021
2021
Unsupervised learning with neural latent variable models
C Nash
The University of Edinburgh, 2020
2020
Relational inductive biases, deep learning, and graph networks (關係歸納偏差, 深度學習和圖形網絡)
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
Modelling 3D Object Shape
C Nash
Generative models of part-structured 3D objects
C Nash, CKI Williams
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학술자료 1–18