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ORCIDDaniel Zoran
Person information
- affiliation: Google DeepMind
- affiliation (former): MIT, CSAIL, Cambridge, MA, USA
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2020 – today
- 2024
[c23]Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner:
SODA: Bottleneck Diffusion Models for Representation Learning. CVPR 2024: 23115-23127- [c22]João Carreira, Michael King, Viorica Patraucean, Dilara Gokay, Catalin Ionescu, Yi Yang, Daniel Zoran, Joseph Heyward, Carl Doersch, Yusuf Aytar, Dima Damen, Andrew Zisserman:
Learning from One Continuous Video Stream. CVPR 2024: 28751-28761 - 2023
- [c21]Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew K. Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo Jimenez Rezende, Daniel Zoran:
Combining Behaviors with the Successor Features Keyboard. NeurIPS 2023 - [i21]Pol Moreno, Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Rosália G. Schneider, Björn Winckler, Larisa Markeeva, Théophane Weber, Danilo J. Rezende:
Laser: Latent Set Representations for 3D Generative Modeling. CoRR abs/2301.05747 (2023) - [i20]Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew Kyle Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo J. Rezende, Daniel Zoran:
Combining Behaviors with the Successor Features Keyboard. CoRR abs/2310.15940 (2023) - [i19]Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner:
SODA: Bottleneck Diffusion Models for Representation Learning. CoRR abs/2311.17901 (2023) - [i18]João Carreira, Michael King, Viorica Patraucean, Dilara Gokay, Catalin Ionescu, Yi Yang, Daniel Zoran, Joseph Heyward, Carl Doersch, Yusuf Aytar, Dima Damen, Andrew Zisserman:
Learning from One Continuous Video Stream. CoRR abs/2312.00598 (2023) - 2022
- [c20]Olivier J. Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, Relja Arandjelovic:
Object Discovery and Representation Networks. ECCV (27) 2022: 123-143 - [c19]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. ICLR 2022 - [i17]João Carreira, Skanda Koppula, Daniel Zoran, Adrià Recasens, Catalin Ionescu, Olivier J. Hénaff, Evan Shelhamer, Relja Arandjelovic, Matthew M. Botvinick, Oriol Vinyals, Karen Simonyan, Andrew Zisserman, Andrew Jaegle:
Hierarchical Perceiver. CoRR abs/2202.10890 (2022) - [i16]Olivier J. Hénaff, Skanda Koppula, Evan Shelhamer, Daniel Zoran, Andrew Jaegle, Andrew Zisserman, João Carreira, Relja Arandjelovic:
Object discovery and representation networks. CoRR abs/2203.08777 (2022) - [i15]Ryan Faulkner, Daniel Zoran:
Solving Reasoning Tasks with a Slot Transformer. CoRR abs/2210.11394 (2022) - 2021
- [c18]Daniel Zoran, Rishabh Kabra, Alexander Lerchner, Danilo J. Rezende:
PARTS: Unsupervised segmentation with slots, attention and independence maximization. ICCV 2021: 10419-10427 - [c17]Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokrá, Danilo Jimenez Rezende:
NeRF-VAE: A Geometry Aware 3D Scene Generative Model. ICML 2021: 5742-5752 - [c16]Rishabh Kabra, Daniel Zoran, Goker Erdogan, Loic Matthey, Antonia Creswell, Matt M. Botvinick, Alexander Lerchner, Christopher P. Burgess:
SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition. NeurIPS 2021: 20146-20159 - [i14]Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokrá, Danilo J. Rezende:
NeRF-VAE: A Geometry Aware 3D Scene Generative Model. CoRR abs/2104.00587 (2021) - [i13]Rishabh Kabra, Daniel Zoran, Goker Erdogan, Loic Matthey, Antonia Creswell, Matthew M. Botvinick, Alexander Lerchner, Christopher P. Burgess:
SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition. CoRR abs/2106.03849 (2021) - [i12]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. CoRR abs/2107.14795 (2021) - 2020
- [c15]Daniel Zoran, Mike Chrzanowski, Po-Sen Huang, Sven Gowal, Alex Mott, Pushmeet Kohli:
Towards Robust Image Classification Using Sequential Attention Models. CVPR 2020: 9480-9489
2010 – 2019
- 2019
- [c14]Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loic Matthey, Matthew M. Botvinick, Alexander Lerchner:
Multi-Object Representation Learning with Iterative Variational Inference. ICML 2019: 2424-2433 - [c13]Alexander Mott, Daniel Zoran, Mike Chrzanowski, Daan Wierstra, Danilo Jimenez Rezende:
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents. NeurIPS 2019: 12329-12338 - [i11]Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loïc Matthey, Matthew M. Botvinick, Alexander Lerchner
:
Multi-Object Representation Learning with Iterative Variational Inference. CoRR abs/1903.00450 (2019) - [i10]Alex Mott, Daniel Zoran, Mike Chrzanowski, Daan Wierstra, Danilo J. Rezende:
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents. CoRR abs/1906.02500 (2019) - [i9]Daniel Zoran, Mike Chrzanowski, Po-Sen Huang, Sven Gowal, Alex Mott, Pushmeet Kohli:
Towards Robust Image Classification Using Sequential Attention Models. CoRR abs/1912.02184 (2019) - 2018
- [c12]Danny Karmon, Daniel Zoran, Yoav Goldberg:
LaVAN: Localized and Visible Adversarial Noise. ICML 2018: 2512-2520 - [i8]Danny Karmon, Daniel Zoran, Yoav Goldberg:
LaVAN: Localized and Visible Adversarial Noise. CoRR abs/1801.02608 (2018) - [i7]Joel Z. Leibo, Cyprien de Masson d'Autume, Daniel Zoran, David Amos, Charles Beattie, Keith Anderson, Antonio García Castañeda, Manuel Sanchez, Simon Green, Audrunas Gruslys, Shane Legg, Demis Hassabis, Matthew M. Botvinick:
Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents. CoRR abs/1801.08116 (2018) - [i6]Avraham Ruderman, Neil C. Rabinowitz, Ari S. Morcos, Daniel Zoran:
Learned Deformation Stability in Convolutional Neural Networks. CoRR abs/1804.04438 (2018) - 2017
- [c11]Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende:
Variational Memory Addressing in Generative Models. NIPS 2017: 3920-3929 - [c10]Nicholas Watters, Daniel Zoran, Theophane Weber, Peter W. Battaglia, Razvan Pascanu, Andrea Tacchetti:
Visual Interaction Networks: Learning a Physics Simulator from Video. NIPS 2017: 4539-4547 - [i5]Daniel Zoran, Balaji Lakshminarayanan, Charles Blundell:
Learning Deep Nearest Neighbor Representations Using Differentiable Boundary Trees. CoRR abs/1702.08833 (2017) - [i4]Nicholas Watters, Andrea Tacchetti, Theophane Weber, Razvan Pascanu, Peter W. Battaglia, Daniel Zoran:
Visual Interaction Networks. CoRR abs/1706.01433 (2017) - [i3]Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende:
Variational Memory Addressing in Generative Models. CoRR abs/1709.07116 (2017) - 2016
- [c9]Katherine L. Bouman, Michael D. Johnson, Daniel Zoran, Vincent L. Fish, Sheperd S. Doeleman, William T. Freeman:
Computational Imaging for VLBI Image Reconstruction. CVPR 2016: 913-922 - 2015
- [c8]Daniel Zoran, Phillip Isola, Dilip Krishnan, William T. Freeman:
Learning Ordinal Relationships for Mid-Level Vision. ICCV 2015: 388-396 - [i2]Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson:
Learning visual groups from co-occurrences in space and time. CoRR abs/1511.06811 (2015) - [i1]Katherine L. Bouman, Michael D. Johnson, Daniel Zoran, Vincent L. Fish, Sheperd S. Doeleman, William T. Freeman:
Computational Imaging for VLBI Image Reconstruction. CoRR abs/1512.01413 (2015) - 2014
- [c7]Phillip Isola, Daniel Zoran, Dilip Krishnan, Edward H. Adelson:
Crisp Boundary Detection Using Pointwise Mutual Information. ECCV (3) 2014: 799-814 - [c6]Daniel Zoran, Dilip Krishnan, José Bento, Bill Freeman:
Shape and Illumination from Shading using the Generic Viewpoint Assumption. NIPS 2014: 226-234 - 2013
- [b1]Daniel Zoran:
Natural image statistics for human and computer vision (שער נוסף בעברית: סטטיסטיקה של תמונות טבעיות עבור ראיית אדם ומכונה.). Hebrew University of Jerusalem, Israel, 2013 - [c5]Dan Rosenbaum, Daniel Zoran, Yair Weiss:
Learning the Local Statistics of Optical Flow. NIPS 2013: 2373-2381 - 2012
- [c4]Daniel Zoran, Yair Weiss:
"Natural Images, Gaussian Mixtures and Dead Leaves". NIPS 2012: 1745-1753 - 2011
- [c3]Daniel Zoran, Yair Weiss:
From learning models of natural image patches to whole image restoration. ICCV 2011: 479-486
2000 – 2009
- 2009
- [c2]Daniel Zoran, Yair Weiss:
Scale invariance and noise in natural images. ICCV 2009: 2209-2216 - [c1]Daniel Zoran, Yair Weiss:
The 'tree-dependent components' of natural scenes are edge filters. NIPS 2009: 2340-2348
Coauthor Index
aka: Danilo J. Rezende
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