Remark: Comparing computation budget under the same setting (1 Tesla V100-32GB, 64 batch size, etc.) on NTU RGB+D 60 Cross-Subject Benchmark. *EfficientNet-B4 requires 4 times higher temporal ...
Abstract: Learning and processing of signals over hypergraph models have gained substantial traction owing to the ability of hypergraphs in characterizing multilateral interactions. In this work, we ...
Abstract: Hypergraph learning has been widely exploited in various image processing applications, due to its advantages in modeling the high-order information. Its efficacy highly depends on building ...
Accurate diagnosis of neurodevelopmental disorders relies on understanding the complex interactions and high-order relationships between brain regions. This work aims to model the subtle, ...
This study introduces a Hybrid Bimodal Model for Analog-to-Digital (ADC) and Digital-to-Analog (DAC) signal conversions, addressing limitations of traditional systems, such as inefficiencies in speed, ...
This paper proposes a hypergraph transformer method for modeling high-order correlations between functional and structural brain networks. By utilizing hypergraphs, we can effectively capture the high ...
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