In traditional deep learning algorithms, one of the key assumptions is t...
Graph Lottery Ticket (GLT), a combination of core subgraph and sparse
su...
Human mobility patterns have shown significant applications in
policy-de...
Forecasting building energy usage is essential for promoting sustainabil...
Decentralized stochastic gradient descent (D-SGD) allows collaborative
l...
In this paper, we strive to develop an interpretable GNNs' inference
par...
Graph Neural Networks (GNNs) have emerged as a powerful category of lear...
Centralized Training with Decentralized Execution (CTDE) has recently em...
Multivariate time series forecasting constitutes important functionality...
Value Decomposition (VD) aims to deduce the contributions of agents for
...
Deep learning technologies have demonstrated remarkable effectiveness in...
Deep cooperative multi-agent reinforcement learning has demonstrated its...
Despite the promising results achieved, state-of-the-art interactive
rei...
The real-time transient stability assessment (TSA) plays a critical role...
Although deep learning has achieved impressive advances in transient
sta...
Graph-level representation learning is the pivotal step for downstream t...
The vast proliferation of sensor devices and Internet of Things enables ...
Multi-modality is an important feature of sensor based activity recognit...
Semi-supervised learning is crucial for alleviating labelling burdens in...
Multimodal features play a key role in wearable sensor-based human activ...
Multimodal features play a key role in wearable sensor based Human Activ...
Person identification technology recognizes individuals by exploiting th...