19 citations · 25 across the 7 of their papers we have counts for
3 papers · 1 filter
Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics
Kenta Oono, Nontawat Charoenphakdee, Kotatsu Bito +14
Virtual Human Generative Model (VHGM) is a generative model that approximates the joint probability over more than 2000 human healthcare-related attributes. This paper presents the…
Einconv: Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks
Kohei Hayashi, Taiki Yamaguchi, Yohei Sugawara +1
Tensor decomposition methods are widely used for model compression and fast inference in convolutional neural networks (CNNs). Although many decompositions are conceivable, only CP…
BayesGrad: Explaining Predictions of Graph Convolutional Networks
Hirotaka Akita, Kosuke Nakago, Tomoki Komatsu +4
Recent advances in graph convolutional networks have significantly improved the performance of chemical predictions, raising a new research question: "how do we explain the predict…