8 citations · 14 across the 9 of their papers we have counts for
9 papers
Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra
Katiana Kontolati, Natalie Klein, Nishant Panda +1
Constructing probability densities for inference in high-dimensional spectral data is often intractable. In this work, we use normalizing flows on structured spectral latent spaces…
Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis
Cory Braker Scott, Eric Mjolsness, Diane Oyen +3
We present a method for learning "spectrally descriptive" edge weights for graphs. We generalize a previously known distance measure on graphs (Graph Diffusion Distance), thereby a…
StressNet: Deep Learning to Predict Stress With Fracture Propagation in Brittle Materials
Yinan Wang, Diane Oyen, Weihong +7
Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal…
Learning Spatial Relationships between Samples of Patent Image Shapes
Juan Castorena, Manish Bhattarai, Diane Oyen
Binary image based classification and retrieval of documents of an intellectual nature is a very challenging problem. Variations in the binary image generation mechanisms which are…
Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning
Manish Bhattarai, Diane Oyen, Juan Castorena +2
Resolution of the complex problem of image retrieval for diagram images has yet to be reached. Deep learning methods continue to excel in the fields of object detection and image c…
TGGLines: A Robust Topological Graph Guided Line Segment Detector for Low Quality Binary Images
Ming Gong, Liping Yang, Catherine Potts +3
Line segment detection is an essential task in computer vision and image analysis, as it is the critical foundation for advanced tasks such as shape modeling and road lane line det…