newsNature Machine IntelligenceTrust 88 · LabPublished 2d agoLive · 22h ago
Multi-resolution enhancement for full-spectrum neural representations
Nature Machine Intelligence, Published online: 24 August 2026; doi:10.1038/s42256-026-01287-9 Ni et al. present WIEN-INR, an implicit neural representation for scientific data compression. It operates in the multiscale wavelet domain to improve compression as well as preserve fine details and signal fidelity.
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 52%EVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain Database →
- PossiblePossibly related (embedding) · 51%Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding →
- PossiblePossibly related (embedding) · 50%NatLabRockies/sup3r →
- PossiblePossibly related (embedding) · 48%Lossless-INR: Lossless Volumetric Implicit Neural Representations →
- PossiblePossibly related (embedding) · 47%SHFormer: Dynamic Spectral Filtering Convolutional Neural Network and High-pass Kernel Generation Transformer for Adaptive MRI Reconstruction →
Covers
paperEVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain DatabasepaperSelf-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz EncodingrepoNatLabRockies/sup3rpaperLossless-INR: Lossless Volumetric Implicit Neural RepresentationspaperSHFormer: Dynamic Spectral Filtering Convolutional Neural Network and High-pass Kernel Generation Transformer for Adaptive MRI Reconstruction
Related across the graph
paperEVOLVE: Efficient Learned Volume Compression with Variable-Rate Encoding on a Cross-Domain DatabasepaperSHFormer: Dynamic Spectral Filtering Convolutional Neural Network and High-pass Kernel Generation Transformer for Adaptive MRI ReconstructionrepoNatLabRockies/sup3rpaperSelf-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz EncodingpaperLossless-INR: Lossless Volumetric Implicit Neural Representations