5 citations · 7 across the 5 of their papers we have counts for
6 papers
Probabilistic Foundations of Fuzzy Simplicial Sets for Nonlinear Dimensionality Reduction
Janis Keck, Lukas Silvester Barth, Fatemeh +3
Fuzzy simplicial sets have become an object of interest in dimensionality reduction and manifold learning, most prominently through their role in UMAP. However, their definition th…
VIBE: Video-Input Brain Encoder for fMRI Response Modeling
Daniel Carlström Schad, Shrey Dixit, Janis Keck +3
We present VIBE, a two-stage Transformer that fuses multi-modal video, audio, and text features to predict fMRI activity. Representations from open-source models (Qwen2.5, BEATs, W…
Frequentist Asymptotics of Variational Laplace
Janis Keck
Variational inference is a general framework to obtain approximations to the posterior distribution in a Bayesian context. In essence, variational inference entails an optimization…
Merging Hazy Sets with m-Schemes: A Geometric Approach to Data Visualization
Lukas Silvester Barth, Hannaneh Fahimi, Parvaneh Joharinad +2
Many machine learning algorithms try to visualize high dimensional metric data in 2D in such a way that the essential geometric and topological features of the data are highlighted…
IsUMap: Manifold Learning and Data Visualization leveraging Vietoris-Rips filtrations
Lukas Silvester Barth, Fatemeh, Fahimi +3
This work introduces IsUMap, a novel manifold learning technique that enhances data representation by integrating aspects of UMAP and Isomap with Vietoris-Rips filtrations. We pres…
Fuzzy simplicial sets and their application to geometric data analysis
Lukas Silvester Barth, Hannaneh Fahimi, Parvaneh Joharinad +3
In this article, we expand upon the concepts introduced by David Spivak about the relationship between the category of uber metric spaces and the category $\mathbf{sF…