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Ayesha Vermani

2 accepted papers

2025

Meta-Dynamical State Space Models for Integrative Neural Data Analysis

ICLR 2025spotlight

Learning shared structure across environments facilitates rapid learning and adaptive behavior in neural systems. This has been widely demonstrated and applied in machine learning to train models that are capable of generalizing to novel settings. However, there has been limited work exploiting the…

Cited by 0SourcePDFScholar
2024

Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data

ICLR 2024poster

Large scale inference models are widely used in neuroscience to extract latent representations from high-dimensional neural recordings. Due to the statistical heterogeneities between sessions and animals, a new model is trained from scratch to infer the underlying dynamics for each new dataset. This…

Cited by 4SourcePDFScholar