network depth

Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth NeurIPS 2020 Universal Approximation with Deep Narrow Networks COLT 2020 Bayesian Learning of Neural Network Architectures AISTATS 2019 Deep, Skinny Neural Networks are not Universal Approximators ICLR 2019 Depth Growing for Neural Machine Translation ACL 2019 LIT: Learned Intermediate Representation Training for Model Compression ICML 2019 Bounds on the Approximation Power of Feedforward Neural Networks ICML 2018 Size-Independent Sample Complexity of Neural Networks COLT 2018 The emergence of spectral universality in deep networks AISTATS 2018 Understanding Deep Neural Networks with Rectified Linear Units ICLR 2018 Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks ICML 2017 On the Expressive Power of Deep Neural Networks ICML 2017 PolyNet: A Pursuit of Structural Diversity in Very Deep Networks CVPR 2017 Convolutional Rectifier Networks as Generalized Tensor Decompositions ICML 2016 Deep Residual Learning for Image Recognition CVPR 2016 Training Very Deep Networks NeurIPS 2015 On the Number of Linear Regions of Deep Neural Networks NeurIPS 2014