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Dar Gilboa
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2020 – today
- 2023
- [c8]Amira Abbas, Robbie King, Hsin-Yuan Huang, William J. Huggins, Ramis Movassagh, Dar Gilboa, Jarrod R. McClean:
On quantum backpropagation, information reuse, and cheating measurement collapse. NeurIPS 2023 - [i9]Amira Abbas, Robbie King, Hsin-Yuan Huang, William J. Huggins, Ramis Movassagh, Dar Gilboa, Jarrod R. McClean:
On quantum backpropagation, information reuse, and cheating measurement collapse. CoRR abs/2305.13362 (2023) - 2021
- [c7]Sam Buchanan, Dar Gilboa, John Wright:
Deep Networks and the Multiple Manifold Problem. ICLR 2021 - [c6]Ari Pakman, Amin Nejatbakhsh, Dar Gilboa, Abdullah Makkeh, Luca Mazzucato, Michael Wibral, Elad Schneidman:
Estimating the Unique Information of Continuous Variables. NeurIPS 2021: 20295-20307 - [c5]Tingran Wang, Sam Buchanan, Dar Gilboa, John Wright:
Deep Networks Provably Classify Data on Curves. NeurIPS 2021: 28940-28953 - [i8]Ari Pakman, Dar Gilboa, Elad Schneidman:
Estimating the Unique Information of Continuous Variables. CoRR abs/2102.00218 (2021) - [i7]Dar Gilboa, Ari Pakman, Thibault Vatter:
Marginalizable Density Models. CoRR abs/2106.04741 (2021) - [i6]Tingran Wang, Sam Buchanan, Dar Gilboa, John Wright:
Deep Networks Provably Classify Data on Curves. CoRR abs/2107.14324 (2021) - 2020
- [b1]Dar Gilboa:
When Can Nonconvex Optimization Problems be Solved with Gradient Descent? A Few Case Studies. Columbia University, USA, 2020 - [c4]Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry:
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization? ICML 2020: 960-969 - [i5]Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry:
Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization? CoRR abs/2007.01038 (2020) - [i4]Sam Buchanan, Dar Gilboa, John Wright:
Deep Networks and the Multiple Manifold Problem. CoRR abs/2008.11245 (2020)
2010 – 2019
- 2019
- [c3]Dar Gilboa, Sam Buchanan, John Wright:
Efficient Dictionary Learning with Gradient Descent. ICML 2019: 2252-2259 - [c2]Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry:
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off. NeurIPS 2019: 7036-7046 - [i3]Dar Gilboa, Bo Chang, Minmin Chen, Greg Yang, Samuel S. Schoenholz, Ed H. Chi, Jeffrey Pennington:
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs. CoRR abs/1901.08987 (2019) - [i2]Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry:
A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off. CoRR abs/1906.00771 (2019) - [i1]Dar Gilboa, Guy Gur-Ari:
Wider Networks Learn Better Features. CoRR abs/1909.11572 (2019) - 2017
- [c1]Ari Pakman, Dar Gilboa, David E. Carlson, Liam Paninski:
Stochastic Bouncy Particle Sampler. ICML 2017: 2741-2750
Coauthor Index
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