spectral bia

Cross-Field Interface-Aware Neural Operators for Multiphase Flow Simulation AAAI 2026 Deeply Seeking Boundary for Lunar Regolith Segmentation AAAI 2026 I-INR: Iterative Implicit Neural Representations AAAI 2026 Implicit Neural Representation with Multi-Scale Sine Activation AAAI 2026 FreqDebias: Towards Generalizable Deepfake Detection via Consistency-Driven Frequency Debiasing CVPR 2025 High-Pass Kernel Prediction for Efficient Video Deblurring WACV 2025 How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings ICLR 2025 Inductive Gradient Adjustment for Spectral Bias in Implicit Neural Representations ICML 2025 On the expressiveness and spectral bias of KANs ICLR 2025 Reduced-rank Factorized Fourier Neural Operator ACML 2025 Transformers Learn Low Sensitivity Functions: Investigations and Implications ICLR 2025 Addressing Spectral Bias of Deep Neural Networks by Multi-Grade Deep Learning NeurIPS 2024 Batch Normalization Alleviates the Spectral Bias in Coordinate Networks CVPR 2024 Can Biases in ImageNet Models Explain Generalization? CVPR 2024 FINER: Flexible Spectral-bias Tuning in Implicit NEural Representation by Variable-periodic Activation Functions CVPR 2024 Improved Implicit Neural Representation with Fourier Reparameterized Training CVPR 2024 On Spectral Properties of Gradient-based Explanation Methods ECCV 2024 ReLUs Are Sufficient for Learning Implicit Neural Representations ICML 2024 The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks NeurIPS 2024 A scalable Walsh-Hadamard regularizer to overcome the low-degree spectral bias of neural networks UAI 2023 DINER: Disorder-Invariant Implicit Neural Representation CVPR 2023 Gaussian Process Surrogate Models for Neural Networks UAI 2023 How much does Initialization Affect Generalization? ICML 2023 Neural Image Compression: Generalization, Robustness, and Spectral Biases NeurIPS 2023 On the spectral bias of two-layer linear networks NeurIPS 2023