Charlie Nash - RankMe

20 papers A* 5A 1Journal 12Unranked 1

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Transframer: Arbitrary Frame Prediction with Generative Models. Trans. Mach. Learn. Res. Charlie Nash, João Carreira, Jacob C. Walker, Iain Barr, Andrew Jaegle, Mateusz Malinowski, Peter W. Battaglia
2022	A*	`conf`	General-purpose, long-context autoregressive modeling with Perceiver AR. ICML Curtis Hawthorne, Andrew Jaegle, Catalina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew M. Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel
2022	J	`jnl`	General-purpose, long-context autoregressive modeling with Perceiver AR. CoRR Curtis Hawthorne, Andrew Jaegle, Catalina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew M. Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel
2022	J	`jnl`	Transframer: Arbitrary Frame Prediction with Generative Models. CoRR Charlie Nash, João Carreira, Jacob C. Walker, Iain Barr, Andrew Jaegle, Mateusz Malinowski, Peter W. Battaglia
2021	J	`jnl`	Generating Images with Sparse Representations. CoRR Charlie Nash, Jacob Menick, Sander Dieleman, Peter W. Battaglia
2021	A*	`conf`	Generating images with sparse representations. ICML Charlie Nash, Jacob Menick, Sander Dieleman, Peter W. Battaglia
2021	A*	`conf`	HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps. CVPR Lu Mi, Hang Zhao, Charlie Nash, Xiaohan Jin, Jiyang Gao, Chen Sun, Cordelia Schmid, Nir Shavit, Yuning Chai, Dragomir Anguelov
2021	J	`jnl`	HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps. CoRR Lu Mi, Hang Zhao, Charlie Nash, Xiaohan Jin, Jiyang Gao, Chen Sun, Cordelia Schmid, Nir Shavit, Yuning Chai, Dragomir Anguelov
2021	J	`jnl`	Variable-rate discrete representation learning. CoRR Sander Dieleman, Charlie Nash, Jesse H. Engel, Karen Simonyan
2020	A*	`conf`	PolyGen: An Autoregressive Generative Model of 3D Meshes. ICML Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter W. Battaglia
2020	J	`jnl`	PolyGen: An Autoregressive Generative Model of 3D Meshes. CoRR Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter W. Battaglia
2020	—	`—`	Unsupervised learning with neural latent variable models. Charlie Nash
2019	A*	`conf`	Autoregressive Energy Machines. ICML Conor Durkan, Charlie Nash
2019	J	`jnl`	Autoregressive Energy Machines. CoRR Charlie Nash, Conor Durkan
2019	J	`jnl`	Efficient Graph Generation with Graph Recurrent Attention Networks. CoRR Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel
2019	A	`conf`	Inverting Supervised Representations with Autoregressive Neural Density Models. AISTATS Charlie Nash, Nate Kushman, Christopher K. I. Williams
2018	J	`jnl`	Autoencoders and Probabilistic Inference with Missing Data: An Exact Solution for The Factor Analysis Case. CoRR Christopher K. I. Williams, Charlie Nash
2018	J	`jnl`	Inverting Supervised Representations with Autoregressive Neural Density Models. CoRR Charlie Nash, Nate Kushman, Christopher K. I. Williams
2017	J	`jnl`	The shape variational autoencoder: A deep generative model of part-segmented 3D objects. Comput. Graph. Forum Charlie Nash, Christopher K. I. Williams
2016	—	`conf`	Overcoming Occlusion with Inverse Graphics. ECCV Workshops (3) Pol Moreno, Christopher K. I. Williams, Charlie Nash, Pushmeet Kohli