Innovation and night light in large and small cities. by Saul Estrin (8629173)

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Geographical distribution of large cities and small cities. by Saul Estrin (8629173)

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The flowchart of the large model for font style transfer. by Weijia Zhu (65481)

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GI-1d-a: Comparison of estimates of people for dataset A (left bar) and B (right bar) per region. The largest discrepancies occur in areas of NE, SE and SW Germany and adjacent reg... by Isabell Schmidt (6331013)

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Assessment values of machine learning models. by Bin Pan (742525)

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Decrease in loss during the training process. by Muhammad Idrees (92773)

Regional contemporary (1990–1999 mean) precipitation and JULES inundation fraction over the Amazon basin. by Nic Gedney (19762301)

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Changes in decadal precipitation and JULES inundation between 1990–1999 and 2089–2098. by Nic Gedney (19762301)

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Contemporary mean inundation fraction in the Amazon basin. by Nic Gedney (19762301)

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Decadal mean regional hydrology. by Nic Gedney (19762301)

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Wetland classification scheme for the contemporary period. by Nic Gedney (19762301)

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Simulated regional mean wetland seasons. by Nic Gedney (19762301)

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Projected decadal changes in seasonality in the hydrological cycle over the wetland regions. by Nic Gedney (19762301)

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Decadal seasonality of the hydrological cycle over the wetland regions. by Nic Gedney (19762301)

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Largest changes in influenza vaccine rates, Pre- vs. Post-COVID-19. by Tyler B. Nofzinger (21560244)

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Nightlight densities in the lowest, around the median and the highest ranked cities in the sample and the distribution of firms in each city. by Saul Estrin (8629173)

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Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”

Machine Learning Models for High Explosive Crystal Density and Performance by Jack V. Davis (9175514)

“…Notably, our model for crystal density surpassed the accuracy of all current models and decreased the root-mean square error (RMSE) of the previous best model by 20%. …”

Penalty conversions yield large practical decreases, but robustness and generalizability of result are limited by data quality and sample selection. by Ryan J. Treves (13527735)

The impact of different diffusion model depths on the model. by Weijia Zhu (65481)

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