2601.11184v1.pdf
Extension
Size
28 MiB
Media Type
application/pdf
SHA-256 is a widely used cryptographic hash function.
This sequence of letters and numbers can be used as a unique identifier for this file
File Hash: SHA-256
94ea6459361a2da3748525cbe87a0d089d06dc55678a62a34b2a50708993648c
Annotations
Structured records describing the file.
Read moreTitle
TimeMar: Multi-Scale Autoregressive Modeling for Unconditional Time Series Generation
Keywords
Time series generation, Autoregressive models, Multiscale modeling
Version
1.7
Page Count
13
Subject
- Computing methodologies -> Machine learning.
Producer
pikepdf 8.15.1
{
"file/base": {
"record": {
"extension": ".pdf",
"hash": "94ea6459361a2da3748525cbe87a0d089d06dc55678a62a34b2a50708993648c",
"media_type": "application/pdf",
"media_type_prefix": "application",
"name": "2601.11184v1.pdf",
"size": 28930202
},
"source": {
"execution_id": "13c82eb6-1a75-4acc-98ea-b141e857eab6",
"id": "file/base",
"type": "Model",
"version": "1.0.0"
}
},
"file/pdf": {
"private": false,
"record": {
"creation_date": "2026-01-19T01:36:21Z",
"keywords": [
"Time series generation",
"Autoregressive models",
"Multiscale modeling"
],
"modified_date": "2026-01-19T01:36:21Z",
"page_count": 13,
"producer": "pikepdf 8.15.1",
"subject": "- Computing methodologies -\u003e Machine learning.",
"title": "TimeMar: Multi-Scale Autoregressive Modeling for Unconditional Time Series Generation",
"version": "1.7"
},
"source": {
"execution_id": "1596710e-967b-4605-80e3-b8d84aa3de02",
"id": "dorsal/pdf",
"type": "Model",
"version": "1.1.0"
}
}
}
The number of unique users who have indexed this public file record
The date this file's metadata was first publicly indexed by any user.
The most recent date this file's metadata was publicly indexed by any user.
File Statistics
- Views:
- 39
- Indexed by:
- 1 user
- Indexed:
- 2026-02-17