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Robust Learning with Implicit Residual Networks
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Geometric Numerical Integration: Structure-Preserving Algorithms for Ordinary Differential Equations
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Computer Vision – ECCV 2018
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Improving DNN Robustness to Adversarial Attacks Using Jacobian Regularization
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Identity Mappings in Deep Residual Networks
inferredcites →https://doi.org/10.1007/978-3-662-12607-3openalex-snapshot
Solving Ordinary Differential Equations I
inferredcites →https://doi.org/10.1007/s10851-019-00903-1openalex-snapshot
Deep Neural Networks Motivated by Partial Differential Equations
inferredcites →https://doi.org/10.1007/s11263-019-01265-2openalex-snapshot
Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities
inferredcites →https://doi.org/10.1007/s40304-017-0103-zopenalex-snapshot
A Proposal on Machine Learning via Dynamical Systems
inferredcites →https://doi.org/10.1016/0005-1098(92)90053-iopenalex-snapshot
Neural networks for control systems—A survey
inferredcites →https://doi.org/10.1016/0378-4754(87)90083-8openalex-snapshot
Solving ordinary differential equations I. nonstiff problems
inferredcites →https://doi.org/10.1016/j.apnum.2007.01.003openalex-snapshot
An estimator for the diagonal of a matrix
inferredcites →https://doi.org/10.1080/03610918908812806openalex-snapshot
A Stochastic Estimator of the Trace of the Influence Matrix for Laplacian Smoothing Splines
inferredcites →https://doi.org/10.1080/03610919008812866openalex-snapshot
A stochastic estimator of the trace of the influence matrix for laplacian smoothing splines
inferredcites →https://doi.org/10.1088/1361-6420/aa9a90openalex-snapshot
Stable architectures for deep neural networks
inferredcites →https://doi.org/10.1103/physrevlett.59.2229openalex-snapshot
Generalization of back-propagation to recurrent neural networks
inferredcites →https://doi.org/10.1109/72.279181openalex-snapshot
Learning long-term dependencies with gradient descent is difficult
inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-snapshot
Densely Connected Convolutional Networks
inferredcites →https://doi.org/10.1109/tsp.2017.2708039openalex-snapshot
Robust Large Margin Deep Neural Networks
inferredcites →https://doi.org/10.1609/aaai.v32i1.11668openalex-snapshot
Reversible Architectures for Arbitrarily Deep Residual Neural Networks
inferredcites →https://doi.org/10.3390/make3010003openalex-snapshot
Robust Learning with Implicit Residual Networks
inferredcites →https://doi.org/10.3390/math7100992openalex-snapshot
Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
inferredcites →https://doi.org/10.48550/arxiv.1603.08029openalex-snapshot
Resnet in Resnet: Generalizing Residual Architectures
inferredcites →https://doi.org/10.48550/arxiv.1704.00028openalex-snapshot
Improved Training of Wasserstein GANs
inferredcites →https://doi.org/10.48550/arxiv.1705.10941openalex-snapshot
Spectral Norm Regularization for Improving the Generalizability of Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.1707.04585openalex-snapshot
The Reversible Residual Network: Backpropagation Without Storing Activations
inferredcites →https://doi.org/10.48550/arxiv.1709.02540openalex-snapshot
The Expressive Power of Neural Networks: A View from the Width
inferredcites →https://doi.org/10.48550/arxiv.1802.04034openalex-snapshot
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1802.05957openalex-snapshot
Spectral Normalization for Generative Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1806.07366openalex-snapshot
Neural Ordinary Differential Equations
inferredcites →https://doi.org/10.48550/arxiv.1810.01367openalex-snapshot
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
inferredcites →https://doi.org/10.48550/arxiv.1903.02639openalex-snapshot
IMEXnet: A Forward Stable Deep Neural Network
inferredcites →https://doi.org/10.48550/arxiv.1908.02729openalex-snapshot
Robust Learning with Jacobian Regularization
inferredcites →https://doi.org/10.48550/arxiv.2002.02798openalex-snapshot
How to train your neural ODE: the world of Jacobian and kinetic regularization
inferredcites →https://doi.org/10.48550/arxiv.2007.04504openalex-snapshot
Learning Differential Equations that are Easy to Solve
inferredcites →https://doi.org/10.5555/2627435.2750359openalex-snapshot
What regularized auto-encoders learn from the data-generating distribution
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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HT-STNet: a hierarchical Tucker decomposition and spatio-temporal LSTM network for accurate and efficient shared mobility demand forecasting on sparse data
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Accuracy and Architecture Studies of Residual Neural Network Method for Ordinary Differential Equations
inferred← citeshttps://doi.org/10.1007/s11227-024-06663-zopenalex-snapshot
Fusion strategies for deep convolutional neural network representations in histopathological image classification
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Time-series learning of latent-space dynamics for reduced-order model closure
inferred← citeshttps://doi.org/10.1109/tce.2025.3565390openalex-snapshot
Implicit Multi-Scale Swin Transformer Network for Image Denoising
inferred← citeshttps://doi.org/10.1142/s0129065727500146openalex-snapshot
Robust and Efficient Neural Architecture Design via Implicit Euler Explicitization
inferred← citeshttps://doi.org/10.1190/segam2021-3594897.1openalex-snapshot
Deep learning for probabilistic salt segmentation using Bayesian inference machines
inferred← citeshttps://doi.org/10.4208/ijnam2024-1026openalex-snapshot
Deep Neural Network for Solving Differential Equations Motivated by Legendre-Galerkin Approximation
inferred← citeshttps://doi.org/10.48550/arxiv.2006.05749openalex-snapshot
Interpolation between Residual and Non-Residual Networks
inferred← citeshttps://doi.org/10.48550/arxiv.2006.10330openalex-snapshot
A Shooting Formulation of Deep Learning
inferred← citeshttps://doi.org/10.48550/arxiv.2101.03583openalex-snapshot
Accuracy and Architecture Studies of Residual Neural Network solving Ordinary Differential Equations
inferred← citeshttps://doi.org/10.48550/arxiv.2305.17155openalex-snapshot
Stability of implicit neural networks for long-term forecasting in dynamical systems
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