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Node and edge dual-masked self-supervised graph representation
Self-supervised graph representation learning has been widely used in many intelligent applications since labeled information can hardly be found in...
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Anisotropic differential concavity codes for palmprint representation
The straight excitatory filters such as Gabor filters and Modified finite Radon transform can not include the vital and inherent curvature...
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Subspace clustering via adaptive-loss regularized representation learning with latent affinities
High-dimensional data that lies on several subspaces tend to be highly correlated and contaminated by various noises, and its affinities across...
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High dimensional model representation median filter for removing salt and pepper noise
In this paper, we introduce a novel method for noise reduction called the High-Dimensional Model Representation (HDMR) Median Filter. HDMR,...
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Predicting drug-drug adverse reactions via multi-view graph contrastive representation model
Predicting drug-drug adverse reactions (DDADRs) is an important task because many patients inevitably take multiple medicines to pursue sound...
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Semantic-enhanced graph neural networks with global context representation
Node classification is a crucial task for efficiently analyzing graph-structured data. Related semi-supervised methods have been extensively studied...
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Hierarchical Graph Representation Learning with Structural Attention for Graph Classification
Recently, graph neural networks (GNNs) exhibit strong expressive power in modeling graph structured data and have been shown to work effectively for...
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Implicit Representation of Relations
We consider implicit representation of an arbitrary family of relations on finite sets. We derive upper and lower bounds for the general cases and...
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Deep structural enhanced network for document clustering
Recently, deep document clustering, which employs deep neural networks to learn semantic document representation for clustering purpose, has...
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Sensorimotor adaptation in virtual reality: Do instructions and body representation influence aftereffects?
Perturbations in virtual reality (VR) lead to sensorimotor adaptation during exposure, but also to aftereffects once the perturbation is no longer...
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Controllable image generation based on causal representation learning
Artificial intelligence generated content (AIGC) has emerged as an indispensable tool for producing large-scale content in various forms, such as...
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Lower-dimensional intrinsic structural representation of leaf images and plant recognition
This paper proposes a statistical representation called “Eigenleaves” for leaf images dependent on their natural structure. The proposed presentation...
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IP2vec: an IP node representation model for IP geolocation
IP geolocation is essential for the territorial analysis of sensitive network entities, location-based services (LBS) and network fraud detection. It...
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A new representation in 3D VLSI floorplan: 3D O-Tree
The size of the implemented circuit plays a vital role in maximizing the performance of the chip. Hence, researchers are looking to utilize the extra...
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How the four-nodes motifs work in heterogeneous node representation?
Heterogeneous information networks (HIN), containing different types of entities with various kinds of interaction relations in between, provide...
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Learning rich feature representation and aggregation for accurate visual tracking
AbstractVisual tracking is a key component of computer vision and has a wide range of practical applications. Recently, the tracking-by-segmentation...
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De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network
Counterfactual inference for continuous rather than binary treatment variables is more common in real-world causal inference tasks. While there are...
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SS-Pro: a simplified Siamese contrastive learning approach for protein surface representation
In this paper, we introduce a simple Siamese contrastive self-supervised learning framework for protein surface representation learning. The encoder...
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Monocular visual-inertial odometry leveraging point-line features with structural constraints
Structural geometry constraints, such as perpendicularity, parallelism and coplanarity, are widely existing in man-made scene, especially in...
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Joint face normalization and representation learning for face recognition
Identity-independent factors, such as variations of pose, expression, illumination, etc., are the key challenges in face recognition. To avoid the...
