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Found 6 papers, 2 papers with code
DDoD: Dual Denial of Decision Attacks on Human-AI Teams
Artificial Intelligence (AI) systems have been increasingly used to make decision-making processes faster, more accurate, and more efficient.
A Survey of Explainable Graph Neural Networks: Taxonomy and Evaluation Metrics
Graph neural networks (GNNs) have demonstrated a significant boost in prediction performance on graph data.
Imitation Learning: Progress, Taxonomies and Challenges
Imitation learning aims to extract knowledge from human experts' demonstrations or artificially created agents in order to replicate their behaviors.
Variational Co-embedding Learning for Attributed Network Clustering
Recent works for attributed network clustering utilize graph convolution to obtain node embeddings and simultaneously perform clustering assignments on the embedding space.
Deep-HOSeq: Deep Higher Order Sequence Fusion for Multimodal Sentiment Analysis
In this research, we first propose a common network to discover both intra-modal and inter-modal dynamics by utilizing basic LSTMs and tensor based convolution networks.
Attn-HybridNet: Improving Discriminability of Hybrid Features with Attention Fusion
The principal component analysis network (PCANet) is an unsupervised parsimonious deep network, utilizing principal components as filters in its convolution layers.
