Avraham Raviv

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All published works

Action	Title	Year	Authors
+ PDF Chat	Formal Verification of Object Detection	2024	Avraham Raviv Yizhak Elboher Michelle Aluf-Medina Y Weiss Omer Cohen Roy Assa Guy Katz Hillel Kugler
+	Layer Folding: Neural Network Depth Reduction using Activation Linearization	2021	Amir Ben Dror Niv Zehngut Avraham Raviv E. Artyomov Ran Vitek Roy J. Jevnisek

Common Coauthors

Coauthor	Papers Together
Hillel Kugler	1
Amir Ben Dror	1
Ran Vitek	1
E. Artyomov	1
Yizhak Elboher	1
Guy Katz	1
Roy J. Jevnisek	1
Michelle Aluf-Medina	1
Niv Zehngut	1
Roy Assa	1
Omer Cohen	1
Y Weiss	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification	2015	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+ PDF Chat	Tensorizing Neural Networks	2015	Alexander Novikov Dmitry Podoprikhin Anton Osokin Dmitry Vetrov	1
+	On the number of response regions of deep feed forward networks with piece-wise linear activations	2013	Razvan Pascanu Guido Montúfar Yoshua Bengio	1
+	On the number of inference regions of deep feed forward networks with piece-wise linear activations	2014	Razvan Pascanu Guido Montúfar Yoshua Bengio	1
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+ PDF Chat	Error bounds for approximations with deep ReLU networks	2017	Dmitry Yarotsky	1
+	Neural Architecture Search with Reinforcement Learning	2016	Barret Zoph Quoc V. Le	1
+	Highway and Residual Networks learn Unrolled Iterative Estimation	2016	Klaus Greff Rupesh K. Srivastava Jürgen Schmidhuber	1
+	Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks	2016	Itay Safran Ohad Shamir	1
+	MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications	2017	Andrew Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand Marco Andreetto Hartwig Adam	1
+	Why Deep Neural Networks for Function Approximation?	2016	Shiyu Liang R. Srikant	1
+	Deep learning generalizes because the parameter-function map is biased towards simple functions	2018	Guillermo Valle-Pérez Chico Q. Camargo Ard A. Louis	1
+	Deep Networks with Stochastic Depth	2016	Gao Huang Yu Sun Zhuang Liu Daniel Sedra Kilian Q. Weinberger	1
+	DARTS: Differentiable Architecture Search	2018	Hanxiao Liu Karen Simonyan Yiming Yang	1
+	Neural Architecture Optimization	2018	Renqian Luo Fei Tian Tao Qin Enhong Chen Tie‐Yan Liu	1
+ PDF Chat	Optimal Approximation with Sparsely Connected Deep Neural Networks	2019	Helmut Bölcskei Philipp Grohs Gitta Kutyniok Philipp Petersen	1
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	1
+	Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications	2015	Yong‐Deok Kim Eunhyeok Park Sungjoo Yoo Tae‐Lim Choi Yang Lu Dongjun Shin	1
+	Benefits of depth in neural networks	2016	Matus Telgarsky	1
+	Speeding-up Convolutional Neural Networks Using Fine-tuned CP-Decomposition	2015	Vadim Lebedev Yaroslav Ganin Maksim Rakhuba Ivan Oseledets Victor Lempitsky	1
+ PDF Chat	NISP: Pruning Networks Using Neuron Importance Score Propagation	2018	Ruichi Yu Ang Li Chun-Fu Chen Jui-Hsin Lai Vlad I. Morariu Xintong Han Mingfei Gao Ching‐Yung Lin Larry S. Davis	1
+ PDF Chat	Optimal approximation of piecewise smooth functions using deep ReLU neural networks	2018	Philipp Petersen Felix Voigtlaender	1
+ PDF Chat	MobileNetV2: Inverted Residuals and Linear Bottlenecks	2018	Mark Sandler Andrew Howard Menglong Zhu Andrey Zhmoginov Liang-Chieh Chen	1
+ PDF Chat	Squeeze-and-Excitation Networks	2019	Jie Hu Li Shen Samuel Albanie Gang Sun Enhua Wu	1
+ PDF Chat	Progressive Neural Architecture Search	2018	Chenxi Liu Barret Zoph Maxim Neumann Jonathon Shlens Hua Wei Li-Jia Li Li Fei-Fei Alan Yuille Jonathan Huang Kevin Murphy	1
+	Regularized Evolution for Image Classifier Architecture Search	2019	Esteban Real Alok Aggarwal Yanping Huang Quoc V. Le	1
+ PDF Chat	FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search	2019	Bichen Wu Kurt Keutzer Xiaoliang Dai Peizhao Zhang Yanghan Wang Fei Sun Yiming Wu Yuandong Tian Péter Vajda Yangqing Jia	1
+	Going in circles is the way forward: the role of recurrence in visual inference	2020	Ruben S. van Bergen Nikolaus Kriegeskorte	1
+ PDF Chat	Single-Path NAS: Designing Hardware-Efficient ConvNets in Less Than 4 Hours	2020	Dimitrios Stamoulis Ruizhou Ding Di Wang Dimitrios Lymberopoulos Bodhi Priyantha Jie Liu Diana Marculescu	1
+ PDF Chat	FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions	2020	Alvin Wan Xiaoliang Dai Peizhao Zhang Zijian He Yuandong Tian Saining Xie Bichen Wu Matthew Yu Tao Xu Kan Chen	1
+	What is the State of Neural Network Pruning	2020	Davis Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John V. Guttag	1
+	Compressing Deep Neural Networks via Layer Fusion	2020	James O’Neill Greg Ver Steeg Aram Galstyan	1
+	Activate or Not: Learning Customized Activation	2020	Ningning Ma Xiangyu Zhang Ming Liu Jian Sun	1
+	Layer Pruning via Fusible Residual Convolutional Block for Deep Neural Networks	2020	Pengtao Xu Jian Cao Fanhua Shang Wenyu Sun Pu Li	1
+	Neural Pruning via Growing Regularization	2020	Huan Wang Can Qin Yulun Zhang Yun Fu	1
+	RepVGG: Making VGG-style ConvNets Great Again	2021	Xiaohan Ding Xiangyu Zhang Ningning Ma Jungong Han Guiguang Ding Jian Sun	1
+	HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search	2021	Niv Nayman Yonathan Aflalo Asaf Noy Lihi Zelnik‐Manor	1
+	DeepReDuce: ReLU Reduction for Fast Private Inference	2021	Nandan Kumar Jha Zahra Ghodsi Siddharth Garg Brandon Reagen	1
+	The Low-Rank Simplicity Bias in Deep Networks	2021	Minyoung Huh Hossein Mobahi Richard Zhang Brian Cheung Pulkit Agrawal Phillip Isola	1