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20162024
most citedMore Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

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Showing 2021Show all

12 papers · 1 filter

cs.CV202129 cited

Nonlocal Patch-Based Fully-Connected Tensor Network Decomposition for Remote Sensing Image Inpainting

Wen-Jie Zheng, Xi-Le Zhao, Yu-Bang Zheng +1

Remote sensing image (RSI) inpainting plays an important role in real applications. Recently, fully-connected tensor network (FCTN) decomposition has been shown the remarkable abil…

cs.SI20214 cited

A Projected Gradient Method for Opinion Optimization with Limited Changes of Susceptibility to Persuasion

Naoki Marumo, Atsushi Miyauchi, Akiko Takeda +1

Many social phenomena are triggered by public opinion that is formed in the process of opinion exchange among individuals. To date, from the engineering point of view, a large body…

cs.LG2021

Application of Adversarial Examples to Physical ECG Signals

Taiga Ono, Takeshi Sugawara, Jun Sakuma +1

This work aims to assess the reality and feasibility of the adversarial attack against cardiac diagnosis system powered by machine learning algorithms. To this end, we introduce ad…

stat.ML2021

Subset-of-Data Variational Inference for Deep Gaussian-Processes Regression

Ayush Jain, P. K. Srijith, Mohammad Emtiyaz Khan

Deep Gaussian Processes (DGPs) are multi-layer, flexible extensions of Gaussian processes but their training remains challenging. Sparse approximations simplify the training but of…

cond-mat.dis-nn202116 cited

Self-learning hybrid Monte Carlo method for isothermal-isobaric ensemble: Application to liquid silica

Keita Kobayashi, Yuki Nagai, Mitsuhiro Itakura +1

Self-learning hybrid Monte Carlo (SLHMC) is a first-principles simulation that allows for exact ensemble generation on potential energy surfaces based on density functional theory.…

nlin.CG2021

Koopman spectral analysis of elementary cellular automata

Keisuke Taga, Yuzuru Kato, Yoshinobu Kawahara +2

We perform a Koopman spectral analysis of elementary cellular automata (ECA). By lifting the system dynamics using a one-hot representation of the system state, we derive a matrix…