Depth Separations in Neural Networks: What is Actually Being Separated?

Depth Separations in Neural Networks: What is Actually Being Separated?

15 April 2019

Papers citing "Depth Separations in Neural Networks: What is Actually Being Separated?"

10 / 10 papers shown

Title
On the Depth of Monotone ReLU Neural Networks and ICNNs Egor Bakaev Florestan Brunck Christoph Hertrich Daniel Reichman Amir Yehudayoff 26 0 0 09 May 2025
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks Eshaan Nichani Alexandru Damian Jason D. Lee MLT 38 13 0 11 May 2023
Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes Christian Haase Christoph Hertrich Georg Loho 28 21 0 24 Feb 2023
Transformers Learn Shortcuts to Automata Bingbin Liu Jordan T. Ash Surbhi Goel A. Krishnamurthy Cyril Zhang OffRL LRM 37 155 0 19 Oct 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 30 29 0 15 Feb 2022
Interplay between depth of neural networks and locality of target functions Takashi Mori Masakuni Ueda 17 0 0 28 Jan 2022
The Connection Between Approximation, Depth Separation and Learnability in Neural Networks Eran Malach Gilad Yehudai Shai Shalev-Shwartz Ohad Shamir 21 20 0 31 Jan 2021
Size and Depth Separation in Approximating Benign Functions with Neural Networks Gal Vardi Daniel Reichman T. Pitassi Ohad Shamir 21 7 0 30 Jan 2021
$Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $ \ell^1 $ and $ \ell^0 $ Controls$ Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $\ell^1$ and $\ell^0$ Controls Jason M. Klusowski Andrew R. Barron 127 142 0 26 Jul 2016
Benefits of depth in neural networks Matus Telgarsky 136 602 0 14 Feb 2016