arXiv subjects

Haoran Xiong

Publications and source records attributed to Haoran Xiong.

7 recordsLinked to original sources

arXiv2026

GRE-Diff: Gaussian Room Embeddings for Structured Layout Diffusion

Designing functional and aesthetically coherent floor plans requires exploring a vast space of possible room arrangements, a task that quickly becomes overwhelming for human designers. In this paper, we propose GRE-Diff, a controllable and interactive diffusion-based framework that automates the creation and editing of apartment floor plans under user-specified constraints. By combining AI-generated suggestions with real-time, human-in-the-loop editing, the system enables users to specify room types, room counts, boundary shapes, and editing operations through LLM-parsed instructions or GUI-based interaction. It then generates a diverse set of plausible and well-structured designs for refinement. At the core of our approach is Gaussian Room Embedding (GRE), a continuous latent representation that models each room as a spatial Gaussian distribution capturing its location and extent. Extensive experiments on the RPLAN dataset show that GRE-Diff produces high-quality, constraint-aware, and editable polygonal layouts, offering a practical step toward bridging AI-driven automation and human creativity in spatial design.

cs.CV↗

arXiv2026

Tur\'{a}n-Theoretic Bounds on Several Elementary Trapping Sets in LDPC Codes

LDPC codes have attracted significant attention due to their capacity-approaching performance. Elementary trapping sets are the main cause of the error floor phenomenon in LDPC codes. We investigate several graph structures associated with trapping sets, including theta graphs, dumbbell graphs, and short cycles with chords. Based on the Tur\'{a}n numbers of $\theta(2,2,2)$, $\theta(1,3,3)$ and $D(4,4;0)$, we prove that any $(a,b)$-ETS in a variable-regular Tanner graph with girth $g=8$ and variable degree $\gamma$ satisfies the inequality $b\geq a\gamma-\frac{a(\sqrt{24a-23}-1)}{4}$, provided that any two 8-cycles in the Tanner graph do not share common variable node. In addition, we can also eliminate ETSs by removing certain short-cycle structures with chords. The lower bounds on the minimum size of ETSs through these methods are improved. To assess practical impact, we analyze spectral radii of the ETSs and construct QC-LDPC codes to show frame error rates in the error floor region.

cs.IT↗

arXiv2025

High-Resolution Retrieval of Atmospheric Boundary Layers with Nonstationary Gaussian Processes

The atmospheric boundary layer (ABL) plays a critical role in governing turbulent exchanges of momentum, heat moisture, and trace gases between the Earth's surface and the free atmosphere, thereby influencing meteorological phenomena, air quality, and climate processes. Accurate and temporally continuous characterization of the ABL structure and height evolution is crucial for both scientific understanding and practical applications. High-resolution retrievals of the ABL height from vertical velocity measurements is challenging because it is often estimated using empirical thresholds applied to profiles of vertical velocity variance or related turbulence diagnostics at each measurement altitude, which can suffer from limited sampling and sensitivity to noise. To address these limitations, this work employs nonstationary Gaussian process (GP) modeling to more effectively capture the spatio-temporal dependence structure in the data, enabling high-quality -- and, if desired, high-resolution -- estimates of the ABL height without reliance on ad-hoc parameter tuning. By leveraging Vecchia approximations, the proposed method can be applied to large-scale datasets, and example applications using full-day vertical velocity profiles comprising approximately $5$M measurements are presented.

physics.ao-ph↗

arXiv2025

The Impact of the Distance Between Cycles on Elementary Trapping Sets

Elementary trapping sets (ETSs) are the main culprits of the performance of low-density parity-check (LDPC) codes in the error floor region. Due to their large quantities and complex structures, ETSs are difficult to analyze. This paper studies the impact of the distance between cycles on ETSs, focusing on two special graph classes: theta graphs and dumbbell graphs, which correspond to cycles with negative and non-negative distances, respectively. We determine the Turán numbers of these graphs and prove that increasing the distance between cycles can eliminate more ETSs. Additionally, using the linear state-space model and spectral theory, we prove that increasing the length of cycles or distance between cycles decreases the spectral radius of the system matrix, thereby reducing the harmfulness of ETSs. This is consistent with the conclusion obtained using Turán numbers. For specific cases when removing two 6-cycles with distance of -1, 0 and 1, respectively, we calculate the sizes, spectral radii, and error probabilities of ETSs. These results confirm that the performance of LDPC codes improves as the distance between cycles increases. Furthermore, we design the PEG-CYCLE algorithm, which greedily maximizes the distance between cycles in the Tanner graph. Numerical results show that the QC-LDPC codes constructed by our method achieve performance comparable to or even superior to state-of-the-art construction methods.

cs.IT↗

arXiv2025

Dimensionality-Reduction Techniques for Approximate Nearest Neighbor Search: A Survey and Evaluation

Approximate Nearest Neighbor Search (ANNS) on high-dimensional vectors has become a fundamental and essential component in various machine learning tasks. Recently, with the rapid development of deep learning models and the applications of Large Language Models (LLMs), the dimensionality of the vectors keeps growing in order to accommodate a richer semantic representation. This poses a major challenge to the ANNS solutions since distance calculation cost in ANNS grows linearly with the dimensionality of vectors. To overcome this challenge, dimensionality-reduction techniques can be leveraged to accelerate the distance calculation in the search process. In this paper, we investigate six dimensionality-reduction techniques that have the potential to improve ANNS solutions, including classical algorithms such as PCA and vector quantization, as well as algorithms based on deep learning approaches. We further describe two frameworks to apply these techniques in the ANNS workflow, and theoretically analyze the time and space costs, as well as the beneficial threshold for the pruning ratio of these techniques. The surveyed techniques are evaluated on six public datasets. The analysis of the results reveals the characteristics of the different families of techniques and provides insights into the promising future research directions.

cs.DB↗

arXiv2024

On the lifting degree of girth-8 QC-LDPC codes

The lifting degree and the deterministic construction of quasi-cyclic low-density parity-check (QC-LDPC) codes have been extensively studied, with many construction methods in the literature, including those based on finite geometry, array-based codes, computer search, and combinatorial techniques. In this paper, we focus on the lifting degree $p$ required for achieving a girth of 8 in $(3,L)$ fully connected QC-LDPC codes, and we propose an improvement over the classical lower bound $p\geq 2L-1$, enhancing it to $p\geq \sqrt{5L^2-11L+\frac{13}{2}}+\frac{1}{2}$. Moreover, we demonstrate that for girth-8 QC-LDPC codes containing an arithmetic row in the exponent matrix, a necessary condition for achieving a girth of 8 is $p\geq \frac{1}{2}L^2+\frac{1}{2}L$. Additionally, we present a corresponding deterministic construction of $(3,L)$ QC-LDPC codes with girth 8 for any $p\geq \frac{1}{2}L^2+\frac{1}{2}L+\lfloor \frac{L-1}{2}\rfloor$, which approaches the lower bound of $\frac{1}{2}L^2+\frac{1}{2}L$. Under the same conditions, this construction achieves a smaller lifting degree compared to prior methods. To the best of our knowledge, the proposed order of lifting degree matches the smallest known, on the order of $\frac{1}{2}L^2+\mathcal{O} (L)$.

cs.IT↗

arXiv2023

Theoretical Bounds for the Size of Elementary Trapping Sets by Graphic Methods

Elementary trapping sets (ETSs) are the main culprits for the performance of LDPC codes in the error floor region. Due to the large quantity, complex structures, and computational difficulties of ETSs, how to eliminate dominant ETSs in designing LDPC codes becomes a pivotal issue to improve the error floor behavior. In practice, researchers commonly address this problem by avoiding some special graph structures to free specific ETSs in Tanner graph. In this paper, we deduce the accurate Turán number of $θ(1,2,2)$ and prove that all $(a,b)$-ETSs in Tanner graph with variable-regular degree $d_L(v)=γ$ must satisfy the bound $b\geq aγ-\frac{1}{2}a^2$, which improves the lower bound obtained by Amirzade when the girth is 6. For the case of girth 8, by limiting the relation between any two 8-cycles in the Tanner graph, we prove a similar inequality $b\geq aγ-\frac{a(\sqrt{8a-7}-1)}{2}$. The simulation results show that the designed codes have good performance with lower error floor over additive white Gaussian noise channels.

cs.IT↗