jacobian matrix

Coherence-based Approximate Derivatives via Web of Affine Spaces Optimization RSS 2025 Time-series attribution maps with regularized contrastive learning AISTATS 2025 Transformer Block Coupling and its Correlation with Generalization in LLMs ICLR 2025 Learning Pseudo-Contractive Denoisers for Inverse Problems ICML 2024 Nuclear Norm Regularization for Deep Learning NeurIPS 2024 Robustly Train Normalizing Flows via KL Divergence Regularization AAAI 2024 Tight and Efficient Upper Bound on Spectral Norm of Convolutional Layers ECCV 2024 Neural Architecture Design and Robustness: A Dataset ICLR 2023 Revisiting Rolling Shutter Bundle Adjustment: Toward Accurate and Fast Solution CVPR 2023 Adversarial Eigen Attack on Black-Box Models CVPR 2022 Constructing Orthogonal Convolutions in an Explicit Manner ICLR 2022 Data-Efficient Augmentation for Training Neural Networks NeurIPS 2022 Neural Tangent Kernel Empowered Federated Learning ICML 2022 DeepLM: Large-Scale Nonlinear Least Squares on Deep Learning Frameworks Using Stochastic Domain Decomposition CVPR 2021 Generalized Comprehensive Motion Theory for High-Order Differential Dynamics RSS 2021 Low-Rank Subspaces in GANs NeurIPS 2021 Coresets for Robust Training of Deep Neural Networks against Noisy Labels NeurIPS 2020 Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks NeurIPS 2019 RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications AAAI 2019 Art of Singular Vectors and Universal Adversarial Perturbations CVPR 2018 Which Neural Net Architectures Give Rise to Exploding and Vanishing Gradients? NeurIPS 2018 Analysis of Deep Neural Networks with Extended Data Jacobian Matrix ICML 2016 Project-Out Cascaded Regression With an Application to Face Alignment CVPR 2015