Dar Gilboa

According to our database, Dar Gilboa authored at least 13 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

On quantum backpropagation, information reuse, and cheating measurement collapse.

Amira Abbas, Robbie King, Hsin-Yuan Huang, William J. Huggins, Ramis Movassagh, Dar Gilboa, Jarrod R. McClean

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

Marginalizable Density Models.

Dar Gilboa, Ari Pakman, Thibault Vatter

CoRR, 2021

Estimating the Unique Information of Continuous Variables.

Ari Pakman, Dar Gilboa, Elad Schneidman

CoRR, 2021

Deep Networks Provably Classify Data on Curves.

Tingran Wang, Sam Buchanan, Dar Gilboa, John Wright

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Estimating the Unique Information of Continuous Variables.

Ari Pakman, Amin Nejatbakhsh, Dar Gilboa, Abdullah Makkeh, Luca Mazzucato, Michael Wibral, Elad Schneidman

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Networks and the Multiple Manifold Problem.

Sam Buchanan, Dar Gilboa, John Wright

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

When Can Nonconvex Optimization Problems be Solved with Gradient Descent? A Few Case Studies.

Dar Gilboa

PhD thesis, 2020

Beyond Signal Propagation: Is Feature Diversity Necessary in Deep Neural Network Initialization?

Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Wider Networks Learn Better Features.

Dar Gilboa, Guy Gur-Ari

CoRR, 2019

Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs.

Dar Gilboa, Bo Chang, Minmin Chen, Greg Yang, Samuel S. Schoenholz, Ed H. Chi, Jeffrey Pennington

CoRR, 2019

A Mean Field Theory of Quantized Deep Networks: The Quantization-Depth Trade-Off.

Yaniv Blumenfeld, Dar Gilboa, Daniel Soudry

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Dictionary Learning with Gradient Descent.

Dar Gilboa, Sam Buchanan, John Wright

Proceedings of the 36th International Conference on Machine Learning, 2019

2017

Stochastic Bouncy Particle Sampler.

Ari Pakman, Dar Gilboa, David E. Carlson, Liam Paninski

Proceedings of the 34th International Conference on Machine Learning, 2017