{"id":13526294,"url":"https://github.com/pratham16cse/DualTPP","last_synced_at":"2025-04-01T07:31:59.778Z","repository":{"id":91996396,"uuid":"297027026","full_name":"pratham16cse/DualTPP","owner":"pratham16cse","description":"Code for \"Long Horizon Forecasting With Temporal Point Processes\", WSDM 2021","archived":false,"fork":false,"pushed_at":"2022-02-05T10:46:26.000Z","size":249732,"stargazers_count":21,"open_issues_count":1,"forks_count":5,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-08-02T06:19:48.962Z","etag":null,"topics":["event-sequence","forecasting","long-term-forecasting","multi-view-learning","point-process","temporal-modeling","temporal-point-processes"],"latest_commit_sha":null,"homepage":"https://arxiv.org/abs/2101.02815","language":"Python","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/pratham16cse.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}},"created_at":"2020-09-20T07:45:12.000Z","updated_at":"2024-03-01T22:34:17.000Z","dependencies_parsed_at":"2023-03-24T01:46:35.687Z","dependency_job_id":null,"html_url":"https://github.com/pratham16cse/DualTPP","commit_stats":{"total_commits":590,"total_committers":12,"mean_commits":"49.166666666666664","dds":0.6338983050847458,"last_synced_commit":"72a806999b828c25929832f7a7fb26244a261711"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pratham16cse%2FDualTPP","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pratham16cse%2FDualTPP/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pratham16cse%2FDualTPP/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pratham16cse%2FDualTPP/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pratham16cse","download_url":"https://codeload.github.com/pratham16cse/DualTPP/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":222709421,"owners_count":17026761,"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":["event-sequence","forecasting","long-term-forecasting","multi-view-learning","point-process","temporal-modeling","temporal-point-processes"],"created_at":"2024-08-01T06:01:27.643Z","updated_at":"2024-11-02T11:30:24.987Z","avatar_url":"https://github.com/pratham16cse.png","language":"Python","funding_links":[],"categories":["Papers"],"sub_categories":["2021"],"readme":"# Long Horizon Forecasting With Temporal Point Processes\n\n![DualTPP Diagram](DualTPP_diagram.png)\n\nThis is the code produced as part of the paper _Long Horizon Forecasting With Temporal Point Processes_ \n\n\u003e \"Long Horizon Forecasting With Temporal Point Processes\"\n\u003e Prathamesh Deshpande, Kamlesh Marathe, Abir De, Sunita Sarawagi. WSDM 2021. [arXiv:2101.02815](https://arxiv.org/abs/2101.02815)\n\n## Packages needed\nSpecified in [requirements](requirements.txt).\n\n## Dataset Download\nWe have provided all the datasets used in our experiments [here](https://drive.google.com/drive/folders/1b1KUwkeIqIViPZoRZzbPAzKeNn7P1OD-?usp=sharing).\n\nPlease download the `data/` folder add place it in the [DualTPP](https://github.com/pratham16cse/DualTPP) directory.\n\n## Experiment execution\nTo run the code to reproduce the results, please use this [script](script.sh) \\[ Under development, more datasets will be soon added to the script\\].\n\n## Output\nAll the outputs will be stored in the `\u003coutput_dir\u003e` directory.\n\nThe numbers reported in Table 2 of the [paper](https://arxiv.org/abs/2101.02815) will be stored in `output_dir/results_\u003cdataset_name\u003e.json` and `output_dir/results_\u003cdataset_name\u003e.txt` files.\n\n## Parameters Description\nUnder Development\n\n## Contact\nFor any queries related to library versions, datasets, script, and results please contact us here:\n\nEmail: prathameshsdeshpande@gmail.com\n\nWhatsapp: +91 9043751980\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpratham16cse%2FDualTPP","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpratham16cse%2FDualTPP","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpratham16cse%2FDualTPP/lists"}