arXiv (All)
open access
ANaLOG: Anisotropic Native-Latent Operator Guidance for Solving Inverse Problems
Native-latent guidance is a recent paradigm for solving inverse problems with latent diffusion models. It replaces repeated evaluations of the image-space forward model, each requiring a decoder pass, with efficient guidance computed using a learned latent-space surrogate. However, existing methods
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Backward SDEs-based Diffusion for Physics-Constrained Generation#1109676
- Variational Autoencoder Inverse Mapper for Extraction of Compton Form Factors: Benchmarks and Conditional Learning#275798
- Physics-Informed Non-Dimensionalisation for Neural Solvers#684012
- Invertible continuous latent dynamic for long-term data assimilation in complex physical systems#1141476
- Orthogonal JEPA: Factorized Predictive States for Latent World Models#471241
Record · ID 1115889
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive