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Tensor factorization via transformed tensor-tensor product for image alignment
In this paper, we study the problem of a batch of linearly correlated image alignment, where the observed images are deformed by some unknown domain...
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Application of Tensor Network Formalism for Processing Tensor Data
Next-generation mobility services require a huge amount of data with multiple attributes. This data is stored as a multi-dimensional array called a...
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Tensor randomized extended Kaczmarz methods for large inconsistent tensor linear equations with t-product
This paper presents three tensor randomized extended Kaczmarz methods for solving a tensor inconsistent linear system of equations under the...
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Low-Rank Tensor Decomposition
Infrared small target detection is a research hotspot in computer vision technology that plays an important role in infrared early warning systems....
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Tensor Iterators for Flexible High-Performance Tensor Computation
The explosive growth of machine learning applications has consequently created a demand for high-performance implementations of tensor contractions,...
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A robust tensor watermarking algorithm for diffusion-tensor images
Watermarking algorithms that use convolution neural networks have exhibited good robustness in studies of deep learning networks. However, after...
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Diffusion tensor image denoising via geometric invariant nonlocal means on the tensor manifold
Diffusion tensor imaging (DTI) is an advanced magnetic resonance technology that describes subtle brain structures using a diffusion tensor at each...
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Compiling Tensor Expressions into Einsum
Tensors are a widely used representations of multidimensional data in scientific and engineering applications. However, efficiently evaluating tensor...
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Convex–Concave Tensor Robust Principal Component Analysis
Tensor robust principal component analysis (TRPCA) aims at recovering the underlying low-rank clean tensor and residual sparse component from the...
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Gradual Tensor Shape Checking
Tensor shape mismatch is a common source of bugs in deep learning programs. We propose a new type-based approach to detect tensor shape mismatches....
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Theories, algorithms and applications in tensor learning
Due to the accelerated development and popularization of Internet, mobile Internet, and Internet of Things and the breakthrough of storage and...
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Image classification based on tensor network DenseNet model
Image classification, the primary domain where deep neural networks significantly contribute to image analysis, requires a substantial amount of...
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LTN: Logic Tensor Networks
In this chapter, we provide an overview of Logic Tensor Networks (LTNs, for short), a formalism that makes use of tensor embeddings—n-dimensional...
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Density peak clustering using tensor network
We introduce a density-based clustering algorithm with tensor networks. In order to demonstrate its effectiveness, we apply it to various types of...
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N-mode minimal tensor extrapolation methods
The purpose of this work is to present, using the n-mode product, a new approach to generalize, for tensor sequences, the well-known vector...
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Tensor completion with noisy side information
We develop a new model for tensor completion which incorporates noisy side information available on the rows and columns of a 3-dimensional tensor....
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Parsimonious mixtures for the analysis of tensor-variate data
Real data is taking on more and more complex structures, raising the necessity for more flexible and parsimonious statistical methodologies....
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Improvement of robust tensor principal component analysis based on generalized nonconvex approach
The problem of nonconvex robust tensor principal component analysis consists of recovering the low-rank and sparse part from a tensor corrupted by...
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THP: Tensor-field-driven hierarchical path planning for autonomous scene exploration with depth sensors
It is challenging to automatically explore an unknown 3D environment with a robot only equipped with depth sensors due to the limited field of view....
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