43 citations · 64 across the 6 of their papers we have counts for
8 papers
Graph Memory: A Structured and Interpretable Framework for Modality-Agnostic Embedding-Based Inference
Artur A. Oliveira, Mateus Espadoto, Roberto M. Cesar +1
We introduce Graph Memory (GM), a structured non-parametric framework that represents an embedding space through a compact graph of reliability-annotated prototype regions. GM enco…
Creating User-steerable Projections with Interactive Semantic Mapping
Artur André Oliveira, Mateus Espadoto, Roberto Hirata +2
Dimensionality reduction (DR) techniques map high-dimensional data into lower-dimensional spaces. Yet, current DR techniques are not designed to explore semantic structure that is…
Relict landslide detection using Deep-Learning architectures for image segmentation in rainforest areas: A new framework
Guilherme P. B. Garcia, Carlos H. Grohmann, Lucas P. Soares +1
Landslides are destructive and recurrent natural disasters on steep slopes and represent a risk to lives and properties. Knowledge of relict landslides location is vital to underst…
UnProjection: Leveraging Inverse-Projections for Visual Analytics of High-Dimensional Data
Mateus Espadoto, Gabriel Appleby, Ashley Suh +6
Projection techniques are often used to visualize high-dimensional data, allowing users to better understand the overall structure of multi-dimensional spaces on a 2D screen. Altho…
HyperNP: Interactive Visual Exploration of Multidimensional Projection Hyperparameters
Gabriel Appleby, Mateus Espadoto, Rui Chen +4
Projection algorithms such as t-SNE or UMAP are useful for the visualization of high dimensional data, but depend on hyperparameters which must be tuned carefully. Unfortunately, i…
On the discovery of stars, quasars, and galaxies in the Southern Hemisphere with S-PLUS DR2
L. Nakazono, C. Mendes de Oliveira, N. S. T. Hirata +25
This paper provides a catalogue of stars, quasars, and galaxies for the Southern Photometric Local Universe Survey Data Release 2 (S-PLUS DR2) in the Stripe 82 region. We show that…