deepinv
importedsoftware/deepinv
DeepInverse: a PyTorch library for solving imaging inverse problems using deep learning
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- BSD-3-Clause(osi)
- Status
- active
- Maturity
- deployed
- Organization
- deepinv
- Country
- unknown
- Homepage
- deepinv.org/
- Repository
- github.com/deepinv/deepinv
- Documentation
- unknown
- Tags
- computational-imaging · deblurring · deep-learning · denoising · diffusion-models · image-reconstruction · medical-imaging · microscopy
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- BayesCapdeblurring · medical-imaging
(ECCV 2022) BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks
- DeepVIDv2denoising · microscopy
DeepVID v2: Self-Supervised Denoising with Decoupled Spatiotemporal Enhancement for Low-Photon Voltage Imaging
- event_super-resolutioncomputational-imaging · microscopy
Repo for Neuromorphic Imaging with Super-Resolution, IEEE TCSVT, 2025.
- FlexSIMcomputational-imaging · microscopy
A flexible SIM reconstruction method capable to handle difficult data prone to reconstruction artifacts.
- FPMcomputational-imaging · microscopy
Matlab simulation of Fourier ptychographic microscopy (FPM).
- phasercomputational-imaging · microscopy
A fully-featured package for multislice electron ptychography
- api.github.com/repos/deepinv/deepinvretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-08-05, 788 stars, license reported as BSD-3-Clause. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/6.json→ .entries["deepinv"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.