2 citations · 8 across the 25 of their papers we have counts for
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stat.ML2023★ 2 cited
The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability
Luca Ambrogioni
Generative diffusion models have achieved spectacular performance in many areas of machine learning and generative modeling. While the fundamental ideas behind these models come fr…
stat.ML2023
Stationarity without mean reversion in improper Gaussian processes
Luca Ambrogioni
The behavior of a GP regression depends on the choice of covariance function. Stationary covariance functions are preferred in machine learning applications. However, (non-periodic…
stat.ML2023
In search of dispersed memories: Generative diffusion models are associative memory networks
Luca Ambrogioni
Uncovering the mechanisms behind long-term memory is one of the most fascinating open problems in neuroscience and artificial intelligence. Artificial associative memory networks h…