arXiv subjects

Miao Huang

Publications and source records attributed to Miao Huang.

8 recordsLinked to original sources

arXiv2025

Referring Camouflaged Object Detection With Multi-Context Overlapped Windows Cross-Attention

Referring camouflaged object detection (Ref-COD) aims to identify hidden objects by incorporating reference information such as images and text descriptions. Previous research has transformed reference images with salient objects into one-dimensional prompts, yielding significant results. We explore ways to enhance performance through multi-context fusion of rich salient image features and camouflaged object features. Therefore, we propose RFMNet, which utilizes features from multiple encoding stages of the reference salient images and performs interactive fusion with the camouflage features at the corresponding encoding stages. Given that the features in salient object images contain abundant object-related detail information, performing feature fusion within local areas is more beneficial for detecting camouflaged objects. Therefore, we propose an Overlapped Windows Cross-attention mechanism to enable the model to focus more attention on the local information matching based on reference features. Besides, we propose the Referring Feature Aggregation (RFA) module to decode and segment the camouflaged objects progressively. Extensive experiments on the Ref-COD benchmark demonstrate that our method achieves state-of-the-art performance.

cs.CV↗

arXiv2025

Accelerated Bayesian Optimal Experimental Design via Conditional Density Estimation and Informative Data

The Design of Experiments (DOEs) is a fundamental scientific methodology that provides researchers with systematic principles and techniques to enhance the validity, reliability, and efficiency of experimental outcomes. In this study, we explore optimal experimental design within a Bayesian framework, utilizing Bayes' theorem to reformulate the utility expectation--originally expressed as a nested double integral--into an independent double integral form, significantly improving numerical efficiency. To further accelerate the computation of the proposed utility expectation, conditional density estimation is employed to approximate the ratio of two Gaussian random fields, while covariance serves as a selection criterion to identify informative datasets during model fitting and integral evaluation. In scenarios characterized by low simulation efficiency and high costs of raw data acquisition, key challenges such as surrogate modeling, failure probability estimation, and parameter inference are systematically restructured within the Bayesian experimental design framework. The effectiveness of the proposed methodology is validated through both theoretical analysis and practical applications, demonstrating its potential for enhancing experimental efficiency and decision-making under uncertainty.

stat.ML↗

arXiv2024

Simulation-based transition density approximation for the inference of SDE models

Stochastic Differential Equations (SDEs) serve as a powerful modeling tool in various scientific domains, including systems science, engineering, and ecological science. While the specific form of SDEs is typically known for a given problem, certain model parameters remain unknown. Efficiently inferring these unknown parameters based on observations of the state in discrete time series represents a vital practical subject. The challenge arises in nonlinear SDEs, where maximum likelihood estimation of parameters is generally unfeasible due to the absence of closed-form expressions for transition and stationary probability density functions of the states. In response to this limitation, we propose a novel two-step parameter inference mechanism. This approach involves a global-search phase followed by a local-refining procedure. The global-search phase is dedicated to identifying the domain of high-value likelihood functions, while the local-refining procedure is specifically designed to enhance the surrogate likelihood within this localized domain. Additionally, we present two simulation-based approximations for the transition density, aiming to efficiently or accurately approximate the likelihood function. Numerical examples illustrate the efficacy of our proposed methodology in achieving posterior parameter estimation.

stat.ME↗

arXiv2024

Energy--Information Trade-off Induces Continuous and Discontinuous Phase Transitions in Lateral Predictive Coding

Lateral predictive coding is a recurrent neural network which creates energy-efficient internal representations by exploiting statistical regularity in sensory inputs. Here we investigate the trade-off between information robustness and energy in a linear model of lateral predictive coding analytically and by numerical minimization of a free energy. We observe several phase transitions in the synaptic weight matrix, especially a continuous transition which breaks reciprocity and permutation symmetry and builds cyclic dominance and a discontinuous transition with the associated sudden emergence of tight balance between excitatory and inhibitory interactions. The optimal network follows an ideal-gas law in an extended temperature range and saturates the efficiency upper-bound of energy utilization. These results bring theoretical insights on the emergence and evolution of complex internal models in predictive processing systems.

q-bio.NC↗

arXiv2020

Rotational excitations in rare-earth nuclei: a comparative study within three cranking models with different mean fields and the treatments of pairing correlations

High-spin rotational bands in rare-earth Er ($Z=68$), Tm ($Z=69$) and Yb ($Z=70$) isotopes are investigated by three different nuclear models. These are (i) the cranked relativistic Hartree-Bogoliubov (CRHB) approach with approximate particle number projection by means of the Lipkin-Nogami (LN) method, (ii) the cranking covariant density functional theory (CDFT) with pairing correlations treated by a shell-model-like approach (SLAP) or the so called particle-number conserving (PNC) method, and (iii) cranked shell model (CSM) based on the Nilsson potential with pairing correlations treated by the PNC method. A detailed comparison between these three models in the description of the ground state rotational bands of even-even Er and Yb isotopes is performed. The similarities and differences between these models in the description of the moments of inertia, the features of band crossings, equilibrium deformations and pairing energies of even-even nuclei under study are discussed. These quantities are considered as a function of rotational frequency and proton and neutron numbers. The changes in the properties of the first band crossings with increasing neutron number in this mass region are investigated. On average, a comparable accuracy of the description of available experimental data is achieved in these models. However, the differences between model predictions become larger above the first band crossings. Because of time-consuming nature of numerical calculations in the CDFT-based models, a systematic study of the rotational properties of both ground state and excited state bands in odd-mass Tm nuclei is carried out only by the PNC-SCM. With few exceptions, the rotational properties of experimental 1-quasiparticle and 3-quasiparticle bands in $^{165,167,169,171}$Tm are reproduced reasonably well.

nucl-th↗

arXiv2019

Configuration and bandhead spin assignments for the 2-quasiparticle rotational bands in the neutron-rich nuclei $^{154, 156}$Pm

The rotational bands in the neutron-rich nuclei $^{153-157}$Pm are investigated by a particle-number conserving method. The kinematic moments of inertia for the 1-quasiparticle bands in odd-$A$ Pm isotopes $^{153, 155, 157}$Pm are reproduced quite well by the present calculation. By comparison between the experimental and calculated moments of inertia for the three 2-quasiparticle bands in the odd-odd nuclei $^{154, 156}$Pm, their configurations and bandhead spins have been assigned properly. For the 2-quasiparticle band in $^{154}$Pm, the configuration is assigned as $\pi5/2^-[532]\otimes \nu3/2^-[521]$ ($K^π=4^+$) with the bandhead spin $I_0=4\hbar$. In $^{156}$Pm, the same configuration and bandhead spin assignments have been made for the 2-quasiparticle band with lower excitation energy. The configuration $\pi5/2^+[413]\otimes \nu5/2^+[642]$ ($K^π=5^+$) with the bandhead spin $I_0=5\hbar$ is assigned for that with higher excitation energy.

nucl-th↗

arXiv2018

Band crossings in $^{168}$Ta: a particle-number conserving analysis

The structures of two observed high-spin rotational bands in the doubly-odd nucleus ${}^{168}$Ta are investigated using the cranked shell model with pairing correlations treated by a particle-number conserving method, in which the blocking effects are taken into account exactly. The experimental moments of inertia and alignments are reproduced very well by the calculations, which confirms the configuration assignments for these two bands in previous works. The backbending and upbending mechanisms in these two bands are analyzed in detail by calculating the occupation probabilities of each orbital close to the Fermi surface and the contributions of each orbital to the total angular momentum alignments. The investigation shows that the level crossings in the first backbending is the neutron $i_{13/2}$ crossing and the in second upbending is the proton $h_{11/2}$ crossing.

nucl-th↗

arXiv2017

Observation of Ten-photon Entanglement Using Thin BiB$_{3}$O$_{6}$ Crystals

We report on the experimental realization of a ten-photon Greenberger-Horne-Zeilinger state using thin BiB$_{3}$O$_{6}$ crystals. The observed fidelity is $0.606\pm0.029$, demonstrating a genuine entanglement with a standard deviation of 3.6 $σ$. This result is further verified using $p$-value calculation, obtaining an upper bound of $3.7\times10^{-3}$ under an assumed hypothesis test. Our experiment paves a new way to efficiently engineer BiB$_{3}$O$_{6}$ crystal-based multi-photon entanglement systems, which provides a promising platform for investigating advanced optical quantum information processing tasks such as boson sampling, quantum error correction and quantum-enhanced measurement.

quant-ph↗