3 papers
cs.LG2023
SAFE: Saliency-Aware Counterfactual Explanations for DNN-based Automated Driving Systems
Amir Samadi, Amir Shirian, Konstantinos Koufos +2
A CF explainer identifies the minimum modifications in the input that would alter the model's output to its complement. In other words, a CF explainer computes the minimum modifica…
cs.SD2023
Heterogeneous Graph Learning for Acoustic Event Classification
Amir Shirian, Mona Ahmadian, Krishna Somandepalli +1
Heterogeneous graphs provide a compact, efficient, and scalable way to model data involving multiple disparate modalities. This makes modeling audiovisual data using heterogeneous…
cs.SD2022
Visually-aware Acoustic Event Detection using Heterogeneous Graphs
Amir Shirian, Krishna Somandepalli, Victor Sanchez +1
Perception of auditory events is inherently multimodal relying on both audio and visual cues. A large number of existing multimodal approaches process each modality using modality-…