deep linear network

Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer ICML 2025 Feature Learning in Finite-Width Bayesian Deep Linear Networks with Multiple Outputs and Convolutional Layers JMLR 2025 Critical Learning Periods Emerge Even in Deep Linear Networks ICLR 2024 Deep linear networks for regression are implicitly regularized towards flat minima NeurIPS 2024 Efficient Low-Dimensional Compression of Overparameterized Models AISTATS 2024 Implicit bias of SGD in L_2-regularized linear DNNs: One-way jumps from high to low rank ICLR 2024 Only Strict Saddles in the Energy Landscape of Predictive Coding Networks? NeurIPS 2024 Theoretical Characterisation of the Gauss Newton Conditioning in Neural Networks NeurIPS 2024 Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss ICML 2023 Deep linear networks can benignly overfit when shallow ones do JMLR 2023 Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data ICML 2023 The Implicit Regularization of Momentum Gradient Descent in Overparametrized Models AAAI 2023 Combining Explicit and Implicit Regularization for Efficient Learning in Deep Networks NeurIPS 2022 Exact learning dynamics of deep linear networks with prior knowledge NeurIPS 2022 Exact Solutions of a Deep Linear Network NeurIPS 2022 Learning dynamics of deep linear networks with multiple pathways NeurIPS 2022 On Non-local Convergence Analysis of Deep Linear Networks ICML 2022 On the Stability and Scalability of Node Perturbation Learning NeurIPS 2022 Analytic Insights into Structure and Rank of Neural Network Hessian Maps NeurIPS 2021 Student-Teacher Learning From Clean Inputs to Noisy Inputs CVPR 2021 Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy NeurIPS 2020 On the Global Convergence of Training Deep Linear ResNets ICLR 2020 Why bigger is not always better: on finite and infinite neural networks ICML 2020 An analytic theory of generalization dynamics and transfer learning in deep linear networks ICLR 2019 Global Convergence of Gradient Descent for Deep Linear Residual Networks NeurIPS 2019