140 citations · 260 across the 14 of their papers we have counts for
4 papers · 1 filter
Multi-view Multi-label Fine-grained Emotion Decoding from Human Brain Activity
Kaicheng Fu, Changde Du, Shengpei Wang +1
Decoding emotional states from human brain activity plays an important role in brain-computer interfaces. Existing emotion decoding methods still have two main limitations: one is…
Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features
Changde Du, Kaicheng Fu, Jinpeng Li +1
Decoding human visual neural representations is a challenging task with great scientific significance in revealing vision-processing mechanisms and developing brain-like intelligen…
Multimodal foundation models are better simulators of the human brain
Haoyu Lu, Qiongyi Zhou, Nanyi Fei +8
Multimodal learning, especially large-scale multimodal pre-training, has developed rapidly over the past few years and led to the greatest advances in artificial intelligence (AI).…
Going Deeper into Permutation-Sensitive Graph Neural Networks
Zhongyu Huang, Yingheng Wang, Chaozhuo Li +1
The invariance to permutations of the adjacency matrix, i.e., graph isomorphism, is an overarching requirement for Graph Neural Networks (GNNs). Conventionally, this prerequisite c…