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Found 6 papers, 1 papers with code
Discovering group dynamics in synchronous time series via hierarchical recurrent switching-state models
Our hierarchical switching recurrent dynamical models can be learned via closed-form variational coordinate ascent updates to all latent chains that scale linearly in the number of individual time series.
Parametric Level-sets Enhanced To Improve Reconstruction (PaLEnTIR)
We introduce PaLEnTIR, a significantly enhanced parametric level-set (PaLS) method addressing the restoration and reconstruction of piecewise constant objects.
Interpretable contrastive word mover's embedding
This paper shows that a popular approach to the supervised embedding of documents for classification, namely, contrastive Word Mover's Embedding, can be significantly enhanced by adding interpretability.
Joint Suzaku and Chandra observations of the MKW4 galaxy group out to the virial radius
We measure an enclosed baryon fraction of 11% at R$_{200}$, remarkably smaller than the cosmic baryon fraction of 15%.
Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics High Energy Astrophysical Phenomena
Automatic coding of students' writing via Contrastive Representation Learning in the Wasserstein space
This work is a step towards building a statistical machine learning (ML) method for achieving an automated support for qualitative analyses of students' writing, here specifically in score laboratory reports in introductory biology for sophistication of argumentation and reasoning.
Large-Scale Automatic Reconstruction of Neuronal Processes from Electron Microscopy Images
Segmentation of large-scale electron microscopy data is the main bottleneck in the analysis of these data sets.
