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Edward J. Smith
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Journal Articles
- 1967
- [j2]Peter Weiner, Edward J. Smith:
On the Number of Distinct State Assignments for Synchronous Sequential Machines. IEEE Trans. Electron. Comput. 16(2): 220-221 (1967) - [j1]Peter Weiner, Edward J. Smith:
Optimization of Reduced Dependencies for Synchronous Sequential Machines. IEEE Trans. Electron. Comput. 16(6): 835-847 (1967)
Conference and Workshop Papers
- 2023
- [c10]Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Gu, Doina Precup, David Meger:
For SALE: State-Action Representation Learning for Deep Reinforcement Learning. NeurIPS 2023 - 2022
- [c9]Omri Puny, Matan Atzmon, Edward J. Smith, Ishan Misra, Aditya Grover, Heli Ben-Hamu, Yaron Lipman:
Frame Averaging for Invariant and Equivariant Network Design. ICLR 2022 - 2021
- [c8]Edward J. Smith, David Meger, Luis Pineda, Roberto Calandra, Jitendra Malik, Adriana Romero-Soriano, Michal Drozdzal:
Active 3D Shape Reconstruction from Vision and Touch. NeurIPS 2021: 16064-16078 - 2020
- [c7]Edward J. Smith, Roberto Calandra, Adriana Romero, Georgia Gkioxari, David Meger, Jitendra Malik, Michal Drozdzal:
3D Shape Reconstruction from Vision and Touch. NeurIPS 2020 - 2019
- [c6]Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger:
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects. ICML 2019: 5866-5876 - [c5]Wenzheng Chen, Huan Ling, Jun Gao, Edward J. Smith, Jaakko Lehtinen, Alec Jacobson, Sanja Fidler:
Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer. NeurIPS 2019: 9605-9616 - 2018
- [c4]Edward J. Smith, Scott Fujimoto, David Meger:
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation. NeurIPS 2018: 6479-6489 - 2017
- [c3]Edward J. Smith, David Meger:
Improved Adversarial Systems for 3D Object Generation and Reconstruction. CoRL 2017: 87-96 - 1966
- [c2]Edward J. Smith, Zvi Kohavi:
Synthesis of Multiple Sequential Machines. SWAT 1966: 160-171 - 1965
- [c1]Zvi Kohavi, Edward J. Smith:
Decomposition of sequential machines. SWCT 1965: 52-61
Informal and Other Publications
- 2023
- [i10]Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Shane Gu, Doina Precup, David Meger
:
For SALE: State-Action Representation Learning for Deep Reinforcement Learning. CoRR abs/2306.02451 (2023) - 2022
- [i9]Edward J. Smith, Michal Drozdzal, Derek Nowrouzezahrai, David Meger
Uncertainty-Driven Active Vision for Implicit Scene Reconstruction. CoRR abs/2210.00978 (2022) - 2021
- [i8]Edward J. Smith, David Meger, Luis Pineda, Roberto Calandra, Jitendra Malik, Adriana Romero, Michal Drozdzal:
Active 3D Shape Reconstruction from Vision and Touch. CoRR abs/2107.09584 (2021) - [i7]Omri Puny, Matan Atzmon, Heli Ben-Hamu, Edward J. Smith, Ishan Misra, Aditya Grover, Yaron Lipman:
Frame Averaging for Invariant and Equivariant Network Design. CoRR abs/2110.03336 (2021) - 2020
- [i6]Edward J. Smith, Roberto Calandra, Adriana Romero, Georgia Gkioxari, David Meger, Jitendra Malik, Michal Drozdzal:
3D Shape Reconstruction from Vision and Touch. CoRR abs/2007.03778 (2020) - 2019
- [i5]Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger:
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects. CoRR abs/1901.11461 (2019) - [i4]Wenzheng Chen, Jun Gao, Huan Ling, Edward J. Smith, Jaakko Lehtinen, Alec Jacobson, Sanja Fidler:
Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer. CoRR abs/1908.01210 (2019) - [i3]Krishna Murthy Jatavallabhula, Edward J. Smith, Jean-Francois Lafleche, Clement Fuji Tsang, Artem Rozantsev, Wenzheng Chen, Tommy Xiang, Rev Lebaredian, Sanja Fidler:
Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research. CoRR abs/1911.05063 (2019) - 2018
- [i2]Edward J. Smith, Scott Fujimoto, David Meger:
3D Object Super-Resolution. CoRR abs/1802.09987 (2018) - 2017
- [i1]Edward J. Smith, David Meger:
Improved Adversarial Systems for 3D Object Generation and Reconstruction. CoRR abs/1707.09557 (2017)
Coauthor Index
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