Search Results for author:
Found 8 papers, 3 papers with code
Unraveling the Temporal Dynamics of the Unet in Diffusion Models
We propose an analytical method to systematically assess the impact of time steps and core Unet components on the final output.
Class-constrained t-SNE: Combining Data Features and Class Probabilities
Data features and class probabilities are two main perspectives when, e. g., evaluating model results and identifying problematic items.
Neural Spherical Harmonics for structurally coherent continuous representation of diffusion MRI signal
We present a novel way to model diffusion magnetic resonance imaging (dMRI) datasets, that benefits from the structural coherence of the human brain while only using data from a single subject.
ProtoFold Neighborhood Inspector
Post-translational modifications (PTMs) affecting a protein's residues (amino acids) can disturb its function, leading to illness.
Incorporating Texture Information into Dimensionality Reduction for High-Dimensional Images
In this paper, we present a method for incorporating spatial neighborhood information into distance-based dimensionality reduction methods, such as t-Distributed Stochastic Neighbor Embedding (t-SNE).
GPGPU Linear Complexity t-SNE Optimization
The t-distributed Stochastic Neighbor Embedding (tSNE) algorithm has become in recent years one of the most used and insightful techniques for the exploratory data analysis of high-dimensional data.
Approximated and User Steerable tSNE for Progressive Visual Analytics
Progressive Visual Analytics aims at improving the interactivity in existing analytics techniques by means of visualization as well as interaction with intermediate results.
Fuzzy Fibers: Uncertainty in dMRI Tractography
Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain.
