Hannah M Christensen
Biographic Data
| ID | 6604353 |
|---|---|
| NAME | Hannah M Christensen |
| GIVEN NAMES | Hannah M |
| FAMILY NAME | Christensen |
| SIGNATURE | CHRISTENSEN H M |
| AFFILIATIONS | University of Chicago |
| ORCID | 0000-0001-8244-0218 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2019 |
| H-INDEX | 0 |
Machine learning and artificial intelligence to aid climate change research and preparedness
Climate change challenges societal functioning, likely requiring considerable adaptation to cope with future altered weather patterns. Machine learning (ML) algorithms have advanced dramatically, triggering breakthroughs in other research sectors, and recently suggested as aiding climate analysis (Reichstein et al 2019 Nature 566 195–204, Schneider et al 2017 Geophys. Res. Lett. 44 12396–417). Although a considerable number of isolated Earth Syst…
Affect and the Limits of Form in Sir Amadace
The Middle English romance Sir Amadace has typically been understood as an illustration of the clash between aristocratic and mercantile economies. This article considers parts of the poem that escape those economies. Drawing on affect theorists, the essay argues that accounts that reduce the narrative to its explicit structures elide crucial poetic elements of affective excess. Amadace maintains a sophisticated tension between structures (whethe…
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Affect and the Limits of Form in Sir Amadace
The Middle English romance Sir Amadace has typically been understood as an illustration of the clash between aristocratic and mercantile economies. This article considers parts of the poem that escape those economies. Drawing on affect theorists, the essay argues that accounts that reduce the narrative to its explicit structures elide crucial poetic elements of affective excess. Amadace maintains a sophisticated tension between structures (whethe…
Machine learning and artificial intelligence to aid climate change research and preparedness
Climate change challenges societal functioning, likely requiring considerable adaptation to cope with future altered weather patterns. Machine learning (ML) algorithms have advanced dramatically, triggering breakthroughs in other research sectors, and recently suggested as aiding climate analysis (Reichstein et al 2019 Nature 566 195–204, Schneider et al 2017 Geophys. Res. Lett. 44 12396–417). Although a considerable number of isolated Earth Syst…
Aesthetics (1 work) · Affect (linguistics (1 work) · Art (1 work) · Artificial Intelligence (1 work) · Atmospheric and Environmental Gas Dynamics (1 work) · Climate change (1 work) · Climate variability and models (1 work) · Communication (1 work) · Communication (1 work) · Computer Science (1 work)