deep learning theory

The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning ICML 2021 Dynamics of Deep Neural Networks and Neural Tangent Hierarchy ICML 2020 Generalized Leverage Score Sampling for Neural Networks NeurIPS 2020 Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning NeurIPS 2020 On Correctness of Automatic Differentiation for Non-Differentiable Functions NeurIPS 2020 On the training dynamics of deep networks with L_2 regularization NeurIPS 2020 Piecewise linear activations substantially shape the loss surfaces of neural networks ICLR 2020 Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth NeurIPS 2020 The phase diagram of approximation rates for deep neural networks NeurIPS 2020 Traces of Class/Cross-Class Structure Pervade Deep Learning Spectra JMLR 2020 Universal Approximation with Deep Narrow Networks COLT 2020 Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks? --- A Neural Tangent Kernel Perspective NeurIPS 2020 Efficient Approximation of Deep ReLU Networks for Functions on Low Dimensional Manifolds NeurIPS 2019 On Connected Sublevel Sets in Deep Learning ICML 2019