190 citations · 585 across the 29 of their papers we have counts for
29 papers
The DESI One-Percent Survey: A concise model for galactic conformity of ELGs
Hongyu Gao, Y. P. Jing, Kun Xu +27
Galactic conformity is the phenomenon in which a galaxy of a certain physical property is correlated with its neighbors of the same property, implying a possible causal relationshi…
Evidence for baryon acoustic oscillations from galaxy-ellipticity correlations
Kun Xu, Y. P. Jing, Gong-Bo Zhao +1
The Baryon Acoustic Oscillations (BAO) feature in the clustering of galaxies or quasars provides a ``standard ruler" for distance measurements in cosmology. In this work, we report…
The DESI One-Percent survey: constructing galaxy-halo connections for ELGs and LRGs using auto and cross correlations
Hongyu Gao, Y. P. Jing, Shanquan Gui +31
In the current Dark Energy Spectroscopic Instrument (DESI) survey, emission line galaxies (ELGs) and luminous red galaxies (LRGs) are essential for mapping the dark matter distribu…
Mass Dependence of Galaxy-Halo Alignment in LOWZ and CMASS
Kun Xu, Y. P. Jing, Hongyu Gao
We measure the galaxy-ellipticity (GI) correlations for the Slogan Digital Sky Survey DR12 LOWZ and CMASS samples with the shape measurements from the DESI Legacy Imaging Surveys.…
PaletteNeRF: Palette-based Color Editing for NeRFs
Qiling Wu, Jianchao Tan, Kun Xu
Neural Radiance Field (NeRF) is a powerful tool to faithfully generate novel views for scenes with only sparse captured images. Despite its strong capability for representing 3D sc…
Modeling and simulation in supersonic three-temperature carbon dioxide turbulent channel flow
Guiyu Cao, Yipeng Shi, Kun Xu +1
This paper pioneers the direct numerical simulation (DNS) and physical analysis in supersonic three-temperature carbon dioxide (CO2) turbulent channel flow. CO2 is a linear and sym…
A study on the Poisson, geometric and Pascal distributions motivated by Chvátal's conjecture
Fu-Bo Li, Kun Xu, Ze-Chun Hu
Let denote a binomial random variable with parameters and . Vasěk Chvátal conjectured that for any fixed , as ranges over , the probabi…
High-order Gas-kinetic Schemes with Non-compact and Compact Reconstruction for Implicit Large Eddy Simulation
Wenjin Zhao, Guiyu Cao, Jianchun Wang +1
High-order gas-kinetic scheme (HGKS) with 5th-order non-compact reconstruction has been well implemented for implicit large eddy simulation (ILES) in nearly incompressible turbulen…
Discourse-Aware Graph Networks for Textual Logical Reasoning
Yinya Huang, Lemao Liu, Kun Xu +3
Textual logical reasoning, especially question-answering (QA) tasks with logical reasoning, requires awareness of particular logical structures. The passage-level logical relations…
Non-equilibrium time-relaxation kinetic model for compressible turbulence modeling
Guiyu Cao, Liang Pan, Kun Xu +2
For the first time, the non-equilibrium time-relaxation kinetic model (NTRKM) is proposed for compressible turbulence modeling on unresolved grids. Within the non-equilibrium time-…
On the Role of Conceptualization in Commonsense Knowledge Graph Construction
Mutian He, Yangqiu Song, Kun Xu +1
Commonsense knowledge graphs (CKGs) like Atomic and ASER are substantially different from conventional KGs as they consist of much larger number of nodes formed by loosely-structur…
A Survey of Adversarial Learning on Graphs
Liang Chen, Jintang Li, Jiaying Peng +6
Deep learning models on graphs have achieved remarkable performance in various graph analysis tasks, e.g., node classification, link prediction, and graph clustering. However, they…
Boosting Adversarial Training with Hypersphere Embedding
Tianyu Pang, Xiao Yang, Yinpeng Dong +3
Adversarial training (AT) is one of the most effective defenses against adversarial attacks for deep learning models. In this work, we advocate incorporating the hypersphere embedd…
Triple Generative Adversarial Networks
Chongxuan Li, Kun Xu, Jiashuo Liu +2
We propose a unified game-theoretical framework to perform classification and conditional image generation given limited supervision. It is formulated as a three-player minimax gam…
Efficient Global String Kernel with Random Features: Beyond Counting Substructures
Lingfei Wu, Ian En-Hsu Yen, Siyu Huo +5
Analysis of large-scale sequential data has been one of the most crucial tasks in areas such as bioinformatics, text, and audio mining. Existing string kernels, however, either (i)…
Understanding and Stabilizing GANs' Training Dynamics with Control Theory
Kun Xu, Chongxuan Li, Jun Zhu +1
Generative adversarial networks (GANs) are effective in generating realistic images but the training is often unstable. There are existing efforts that model the training dynamics…
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
Tianyu Pang, Kun Xu, Jun Zhu
It has been widely recognized that adversarial examples can be easily crafted to fool deep networks, which mainly root from the locally non-linear behavior nearby input examples. A…
Multi-objects Generation with Amortized Structural Regularization
Kun Xu, Chongxuan Li, Jun Zhu +1
Deep generative models (DGMs) have shown promise in image generation. However, most of the existing work learn the model by simply optimizing a divergence between the marginal dist…
Lattice CNNs for Matching Based Chinese Question Answering
Yuxuan Lai, Yansong Feng, Xiaohan Yu +3
Short text matching often faces the challenges that there are great word mismatch and expression diversity between the two texts, which would be further aggravated in languages lik…
Improved Decoding of Staircase Codes: The Soft-aided Bit-marking (SABM) Algorithm
Yi Lei, Bin Chen, Gabriele Liga +5
Staircase codes (SCCs) are typically decoded using iterative bounded-distance decoding (BDD) and hard decisions. In this paper, a novel decoding algorithm is proposed, which partia…
Improving Adversarial Robustness via Promoting Ensemble Diversity
Tianyu Pang, Kun Xu, Chao Du +2
Though deep neural networks have achieved significant progress on various tasks, often enhanced by model ensemble, existing high-performance models can be vulnerable to adversarial…
To Relieve Your Headache of Training an MRF, Take AdVIL
Chongxuan Li, Chao Du, Kun Xu +3
We propose a black-box algorithm called {\it Adversarial Variational Inference and Learning} (AdVIL) to perform inference and learning on a general Markov random field (MRF). AdVIL…
Decoding Staircase Codes with Marked Bits
Yi Lei, Alex Alvarado, Bin Chen +4
Staircase codes (SCCs) are typically decoded using iterative bounded-distance decoding (BDD) and hard decisions. In this paper, a novel decoding algorithm is proposed, which partia…
SQL-to-Text Generation with Graph-to-Sequence Model
Kun Xu, Lingfei Wu, Zhiguo Wang +2
Previous work approaches the SQL-to-text generation task using vanilla Seq2Seq models, which may not fully capture the inherent graph-structured information in SQL query. In this p…