Julius Vetter

Jun 27, 2024 | arxiv.org | Auguste Schulz |Julius Vetter |Richard Gao |Felix Pei

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Apr 25, 2024 | biorxiv.org | Auguste Schulz |Julius Vetter |Richard Gao |Daniel Morales

AbstractExtracting the relationship between high-dimensional recordings of neural activity and complex behavior is a ubiquitous problem in systems neuroscience. Toward this goal, encoding and decoding models attempt to infer the conditional distribution of neural activity given behavior and vice versa, while dimensionality reduction techniques aim to extract interpretable low-dimensional representations.

Aug 24, 2023 | biorxiv.org | Jakob H. Macke |Richard Gao |Julius Vetter

AbstractIn recent years, deep generative models have had a profound impact in engineering and sciences, revolutionizing domains such as image and audio generation, as well as advancing our ability to model scientific data. In particular, Denoising Diffusion Probabilistic Models (DDPMs) have been shown to accurately model time series as complex high-dimensional probability distributions.