{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/random-mesh-projectors-for-inverse-problems","title":"Random mesh projectors for inverse problems","arxiv_id":"1805.11718","date":"2018-05-29","proceeding":"ICLR 2019 5","authors":["Sidharth Gupta","Konik Kothari","Maarten V. de Hoop","Ivan Dokmanić"],"abstract":"We propose a new learning-based approach to solve ill-posed inverse problems\nin imaging. We address the case where ground truth training samples are rare\nand the problem is severely ill-posed - both because of the underlying physics\nand because we can only get few measurements. This setting is common in\ngeophysical imaging and remote sensing. We show that in this case the common\napproach to directly learn the mapping from the measured data to the\nreconstruction becomes unstable. Instead, we propose to first learn an ensemble\nof simpler mappings from the data to projections of the unknown image into\nrandom piecewise-constant subspaces. We then combine the projections to form a\nfinal reconstruction by solving a deconvolution-like problem. We show\nexperimentally that the proposed method is more robust to measurement noise and\ncorruptions not seen during training than a directly learned inverse.","url_abs":"http://arxiv.org/abs/1805.11718v3","url_pdf":"http://arxiv.org/pdf/1805.11718v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"random-mesh-projectors-for-inverse-problems","repo_url":"https://github.com/swing-research/deepmesh","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.11718","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1805.11718"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/swing-research/deepmesh","reach":null}],"summary":{"unverified":1},"by_repo_kind":{"official":{"samples":1,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"1f6d077e56661c9a","entry":"get_P_Pinv","repo":"swing-research/deepmesh","repo_kind":"official","path":"projnet/train_projnets.py","file_url":"https://github.com/swing-research/deepmesh/blob/HEAD/projnet/train_projnets.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"1f6d077e56661c9a"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}