{"id":16130160,"url":"https://github.com/aksub99/dl-papers","last_synced_at":"2025-04-06T14:14:54.147Z","repository":{"id":129521144,"uuid":"165851573","full_name":"aksub99/DL-papers","owner":"aksub99","description":"Papers I am currently reading/implementing or have read/implemented.","archived":false,"fork":false,"pushed_at":"2019-05-21T14:34:37.000Z","size":1279,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-02-12T20:17:22.230Z","etag":null,"topics":["computer-vision","deep-learning","notes"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/aksub99.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-01-15T13:01:15.000Z","updated_at":"2019-09-06T01:40:37.000Z","dependencies_parsed_at":"2023-06-12T00:30:40.833Z","dependency_job_id":null,"html_url":"https://github.com/aksub99/DL-papers","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aksub99%2FDL-papers","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aksub99%2FDL-papers/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aksub99%2FDL-papers/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aksub99%2FDL-papers/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aksub99","download_url":"https://codeload.github.com/aksub99/DL-papers/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247492543,"owners_count":20947545,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["computer-vision","deep-learning","notes"],"created_at":"2024-10-09T22:14:53.319Z","updated_at":"2025-04-06T14:14:54.127Z","avatar_url":"https://github.com/aksub99.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Papers I have read and/or implemented:\n1)Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces  \n  https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.98.146401  \n  \n2)Cross-language framework for word recognition and spotting of Indic scripts  \n  https://www.sciencedirect.com/science/article/pii/S0031320318300463#bib0020  \n\n3)U-Net: Convolutional Networks for Biomedical Image Segmentation  \n  https://arxiv.org/abs/1505.04597  \n\n4)TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation  \n  https://arxiv.org/abs/1801.05746  \n\n5)Feature Pyramid Networks for Object Detection  \n  https://arxiv.org/abs/1612.03144  \n\n6)Focal Loss for Dense Object Detection  \n  https://arxiv.org/abs/1708.02002  \n\n7)MT-CGCNN: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction  \n  https://arxiv.org/abs/1811.05660  \n\n8)BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding  \n  https://arxiv.org/abs/1810.04805  \n\n9)Attention Is All You Need  \n  https://arxiv.org/abs/1706.03762  \n\n10)Single-Shot Refinement Neural Network for Object Detection  \n  https://arxiv.org/abs/1711.06897  \n\n11)Automatic chemical design using a data-driven continuous representation of molecules  \n  https://arxiv.org/abs/1610.02415  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faksub99%2Fdl-papers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faksub99%2Fdl-papers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faksub99%2Fdl-papers/lists"}