Jonathan Larson
Biographic Data
| ID | 8486312 |
|---|---|
| NAME | Jonathan Larson |
| GIVEN NAMES | Jonathan |
| FAMILY NAME | Larson |
| SIGNATURE | LARSON J |
| AFFILIATIONS | Microsoft (United States) |
| ORCID | 0000-0002-8865-9306 |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Refined graph encoder embedding via self-training and latent community recovery
This paper introduces a refined graph encoder embedding method, enhancing the original graph encoder embedding through linear transformation, self-training, and hidden community recovery within observed communities. We provide the theoretical rationale for the refinement procedure, demonstrating how and why our proposed method can effectively identify useful hidden communities under stochastic block models. Furthermore, we show how the refinement…
Critical Thinking in Slovakia after Socialism
Critical thinking is considered the civic virtue of a liberal democracy. Citizens who think for themselves, cooperate, and can agree to disagree are the hallmark of a self-governing society. Citizens of nondemocratic societies, however, are believed to lack this virtue. Authoritarian regimes, it is thought, smother critical discourse through fear and dull critical thought through the control of information and dissemination of propaganda. Since t…
No prominent works on this page.
Critical Thinking in Slovakia after Socialism
Critical thinking is considered the civic virtue of a liberal democracy. Citizens who think for themselves, cooperate, and can agree to disagree are the hallmark of a self-governing society. Citizens of nondemocratic societies, however, are believed to lack this virtue. Authoritarian regimes, it is thought, smother critical discourse through fear and dull critical thought through the control of information and dissemination of propaganda. Since t…
Refined graph encoder embedding via self-training and latent community recovery
This paper introduces a refined graph encoder embedding method, enhancing the original graph encoder embedding through linear transformation, self-training, and hidden community recovery within observed communities. We provide the theoretical rationale for the refinement procedure, demonstrating how and why our proposed method can effectively identify useful hidden communities under stochastic block models. Furthermore, we show how the refinement…
Advanced Graph Neural Networks (1 work) · Artificial Intelligence (1 work) · Civil society (1 work) · Communism (1 work) · Complex Network Analysis Techniques (1 work) · Computer Science (1 work) · Critical thinking (1 work) · Eastern European Communism and Reforms (1 work) · Embedding (1 work) · Encoder (1 work)