- Title Information
- Title
- Supplement for Symmetries and Gradient Flows in the Deep Linear Network
- Type of Resource (primo)
- research_datasets
- Abstract
- This repository is the companion archive of selected and annotated LLM conversations for Tejas Kotwal's thesis, "Symmetries and Gradient Flows in the Deep Linear Network" (Brown University, 2026). The repository documents research process rather than mathematical authority. The transcripts show examples, false starts, convention checks, editorial experiments, and local calculations that helped shape parts of the thesis. No theorem, formula, definition, or attribution should be accepted because it appears in a model response. Each surviving mathematical point was checked separately before it was used in the thesis. The archive is selective rather than exhaustive. It follows the standard described in Section 1.4 of the thesis: each public conversation is accompanied by a note explaining the mathematical question, what was already known or drafted before the exchange, what the model contributed, where it failed or overreached, how the material was checked, and how it affected the thesis.
- Name
- Name Part
- Kotwal, Tejas
- Role
- Role Term (marcrelator)
(authorityURI="http://id.loc.gov/vocabulary/relators", valueURI="http://id.loc.gov/vocabulary/relators/cre")
- Creator
- Origin Information
- Date Created
- 2026
- Subject (Local)
- Topic
- Deep Linear Networks
- Genre
- datasets
- Access Condition:
use and reproduction
- All rights reserved
- Access Condition:
rights statement
(href="http://rightsstatements.org/vocab/InC/1.0/")
- In Copyright
- Access Condition:
restriction on access
- All Rights Reserved
- Identifier:
DOI
- 10.26300/3zq2-0864