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Direction-of-Arrival (DOA) estimation in sensor arrays faces limitations under demanding conditions, including low signal-to-noise ratio, single-snapshot scenarios, coherent sources, and unknown source counts. Conventional beamforming…

Signal Processing · Electrical Eng. & Systems 2025-10-14 Xuyao Deng , Yong Dou , Kele Xu

We show that de-focused single particle images recorded using a cryo-electron microscope (cryoEM) system may be processed like a Fresnel zone in-line hologram to obtain physically meaningful quantitative phase maps associated with…

Image and Video Processing · Electrical Eng. & Systems 2021-11-24 Apoorv Pant , Manidipa Banerjee , Kedar Khare

Supervised fine-tuning (SFT) is a crucial step for adapting large language models (LLMs) to downstream tasks. However, conflicting objectives across heterogeneous SFT tasks often induce the "seesaw effect": optimizing for one task may…

Computation and Language · Computer Science 2026-01-27 Xiaoyu Liu , Xiaoyu Guan , Di Liang , Xianjie Wu

Single-photon Lidar imaging offers a significant advantage in 3D imaging due to its high resolution and long-range capabilities, however it is challenging to apply in noisy environments with multiple targets per pixel. To tackle these…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Kyungmin Choi , JaKeoung Koo , Stephen McLaughlin , Abderrahim Halimi

We present the first mathematical analysis of stochastic density functional theory (DFT) in the context of the Hartree approximation. We motivate our analysis via the notion of nearly-optimal or $\tilde{O}(n)$ scaling with respect to the…

Numerical Analysis · Mathematics 2025-06-03 Yuhang Cai , Michael Lindsey

Scanning transmission electron microscopy (STEM) is a powerful tool to reveal the morphologies and structures of materials, thereby attracting intensive interests from the scientific and industrial communities. The outstanding spatial…

Image and Video Processing · Electrical Eng. & Systems 2024-09-26 Hanlei Zhang , Jincheng Bai , Xiabo Chen , Can Li , Chuanjian Zhong , Jiye Fang , Guangwen Zhou

Cryo Focused Ion-Beam Scanning Electron Microscopy (cryo FIB-SEM) enables three-dimensional and nanoscale imaging of biological specimens via a slice and view mechanism. The FIB-SEM experiments are, however, limited by a slow (typically,…

We present a Gaussian-basis implementation of orbital-free density-functional theory (OF-DFT) in which the trust-region image method (TRIM) is used for optimization. This second-order optimization scheme has been constructed to provide…

Chemical Physics · Physics 2021-09-15 Matthew S. Ryley , Michael Withnall , Tom J. P. Irons , Trygve Helgaker , Andrew M. Teale

Density Functional Theory (DFT) allows for predicting all the chemical and physical properties of molecular systems from first principles by finding an approximate solution to the many-body Schr\"odinger equation. However, the cost of these…

Machine Learning · Computer Science 2025-06-03 Majdi Hassan , Cristian Gabellini , Hatem Helal , Dominique Beaini , Kirill Neklyudov

Motivation: Structural heterogeneity in single-particle cryo-electron microscopy (cryo-EM) data represents a major challenge for high-resolution structure determination. Unsupervised classification may serve as the first step in the…

Data Analysis, Statistics and Probability · Physics 2017-11-01 Jiayi Wu , Yong-Bei Ma , Charles Congdon , Bevin Brett , Shuobing Chen , Qi Ouyang , Youdong Mao

Direct detector device (DDD) cameras have revolutionized single particle electron cryomicroscopy (cryo-EM). In addition to an improved camera detective quantum efficiency, acquisition of DDD movies allows for correction of movement of the…

Quantitative Methods · Quantitative Biology 2015-11-23 John L. Rubinstein , Marcus A. Brubaker

The contrast transfer function (CTF) is widely used to evaluate phase retrieval methods in scanning transmission electron microscopy (STEM), including center-of-mass imaging, parallax imaging, direct ptychography, and iterative…

Cryo-electron microscopy (cryo-EM) studies using single particle reconstruction are extensively used to reveal structural information on macromolecular complexes. Aiming at the highest achievable resolution, state of the art electron…

The sparse-group lasso performs both variable and group selection, simultaneously using the strengths of the lasso and group lasso. It has found widespread use in genetics, a field that regularly involves the analysis of high-dimensional…

Machine Learning · Statistics 2025-09-18 Fabio Feser , Marina Evangelou

In the field of non-invasive medical imaging, radiomic features are utilized to measure tumor characteristics. However, these features can be affected by the techniques used to discretize the images, ultimately impacting the accuracy of…

Image and Video Processing · Electrical Eng. & Systems 2025-11-06 Wenhao Chi , Haiping Liu , Hongqiao Dong , Wenhua Liang , Bo Liu

Spectroscopic properties of molecules holds great importance for the description of the molecular response under the effect of an UV/Vis electromagnetic radiation. Computationally expensive ab initio (e.g. MultiConfigurational SCF, Coupled…

In this work, we present the convergence analysis of one-point large deviations rate functions (LDRFs) of the spatial finite difference method (FDM) for stochastic wave equations with small noise, which is essentially about the asymptotical…

Numerical Analysis · Mathematics 2022-09-20 Diancong Jin , Jialin Hong , Derui Sheng

Deep learning-based methods monopolize the latest research in the field of thermal infrared (TIR) object tracking. However, relying solely on deep learning models to obtain better tracking results requires carefully selecting feature…

Computer Vision and Pattern Recognition · Computer Science 2024-07-29 Peng Gao , Shi-Min Li , Feng Gao , Fei Wang , Ru-Yue Yuan , Hamido Fujita

Cryo-electron microscopy (cryo-EM) extracts single-particle density projections of individual biomolecules. Although cryo-EM is widely used for 3D reconstruction, due to its single-particle nature, it has the potential to provide…

Learning a Gaussian Mixture Model (GMM) is hard when the number of parameters is too large given the amount of available data. As a remedy, we propose restricting the GMM to a Gaussian Markov Random Field Mixture Model (GMRF-MM), as well as…

Machine Learning · Computer Science 2022-01-25 Shahaf E. Finder , Eran Treister , Oren Freifeld