74 citations · 227 across the 21 of their papers we have counts for
29 papers
Action Segmentation with Mixed Temporal Domain Adaptation
Min-Hung Chen, Baopu Li, Yingze Bao +1
The main progress for action segmentation comes from densely-annotated data for fully-supervised learning. Since manual annotation for frame-level actions is time-consuming and cha…
Joint Learning for Spatial Context-based Seismic Inversion of Multiple Datasets for Improved Generalizability and Robustness
Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
Seismic inversion plays a very useful role in detailed stratigraphic interpretation of seismic data. Seismic inversion enables estimation of rock properties over the complete seism…
Contrastive Reasoning in Neural Networks
Mohit Prabhushankar, Ghassan AlRegib
Neural networks represent data as projections on trained weights in a high dimensional manifold. The trained weights act as a knowledge base consisting of causal class dependencies…
Extracting Causal Visual Features for Limited label Classification
Mohit Prabhushankar, Ghassan AlRegib
Neural networks trained to classify images do so by identifying features that allow them to distinguish between classes. These sets of features are either causal or context depende…
Self-Supervised Annotation of Seismic Images using Latent Space Factorization
Oluwaseun Joseph Aribido, Ghassan AlRegib, Mohamed Deriche
Annotating seismic data is expensive, laborious and subjective due to the number of years required for seismic interpreters to attain proficiency in interpretation. In this paper,…
Gradients as a Measure of Uncertainty in Neural Networks
Jinsol Lee, Ghassan AlRegib
Despite tremendous success of modern neural networks, they are known to be overconfident even when the model encounters inputs with unfamiliar conditions. Detecting such inputs is…