Generative models and uncertainty quantification 2023
PulseAugur coverage of Generative models and uncertainty quantification 2023 — every cluster mentioning Generative models and uncertainty quantification 2023 across labs, papers, and developer communities, ranked by signal.
No coverage in the last 90 days.
3 day(s) with sentiment data
-
AI hallucinations in imaging linked to inverse problem limits
Researchers have developed a theoretical framework to understand and quantify "hallucinations" in AI models used for inverse problems, such as medical imaging. The study shows that these realistic but incorrect details …
-
Generative models learn rules across two distinct training timescales
Researchers have identified two distinct timescales in generative model training: the point at which generations become rule-valid ($\tau_{\mathrm{rule}}$) and the point at which models begin reproducing training sample…
-
AI models can avoid output collapse with diverse reward functions
A new theoretical study explores how generative models can avoid collapsing into narrow output ranges during recursive retraining. Researchers propose that using multiple, diverse reward functions for data curation, rat…