papers

Publications (14)

quant-ph2020

Quantum enhanced optical phase estimation with a squeezed thermal state

Juan Yu, Yue Qin, Jinliang Qin +4

Quantum phase estimation protocols can provide a measuring method of phase shift with precision superior to standard quantum limit (SQL) due to the application of a nonclassical st…

eess.SY2020

Data-Driven Assisted Chance-Constrained Energy and Reserve Scheduling with Wind Curtailment

Xingyu Lei, Zhifang Yang, Junbo Zhao +1

Chance-constrained optimization (CCO) has been widely used for uncertainty management in power system operation. With the prevalence of wind energy, it becomes possible to consider…

eess.SY2020

Data-driven Optimal Power Flow: A Physics-Informed Machine Learning Approach

Xingyu Lei, Zhifang Yang, Juan Yu +3

This paper proposes a data-driven approach for optimal power flow (OPF) based on the stacked extreme learning machine (SELM) framework. SELM has a fast training speed and does not…

quant-ph2020

Nonlinear Improvement of Qubit-qudit Entanglement Witnesses

Shu-Qian Shen, Jin-Min Liang, Ming Li +2

The entanglement witness is an important and experimentally applicable tool for entanglement detection. In this paper, we provide a nonlinear improvement of any entanglement witnes…

quant-ph2016

Improved Separability Criteria Based on Bloch Representation of Density Matrices

Shu-Qian Shen, Juan Yu, Ming Li +1

The correlation matrices or tensors in the Bloch representation of density matrices are encoded with entanglement properties. In this paper, based on the Bloch representation of de…

q-bio.TO2025

Mammo-Clustering: Context Clustering based Multi-view Tri Level Information Fusion for Lesion Location and Classification in Mammography

Shilong Yang, Chulong Zhang, Xiaokun Liang +9

Breast cancer is a significant global health issue, and the diagnosis of breast cancer through imaging remains challenging. Mammography images are characterized by extremely high r…

eess.SP2019

Fast Calculation of Probabilistic Power Flow: A Model-based Deep Learning Approach

Yan Yang, Zhifang Yang, Juan Yu +1

Probabilistic power flow (PPF) plays a critical role in power system analysis. However, the high computational burden makes it challenging for the practical implementation of PPF.…

cs.LG2026

Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning

NVIDIA, :, Aakshita Chandiramani +544

We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemo…

cs.CV2026

Visualizing the Invisible: Enhancing Radiologist Performance in Breast Mammography via Task-Driven Chromatic Encoding

Hui Ye, Shilong Yang, Chulong Zhang +4

Purpose:Mammography screening is less sensitive in dense breasts, where tissue overlap and subtle findings increase perceptual difficulty. We present MammoColor, an end-to-end fram…

cs.CV2026

Data-Efficient Meningioma Segmentation via Implicit Spatiotemporal Mixing and Sim2Real Semantic Injection

Yunhao Xu, Fuquan Zong, Yexuan Xing +5

The performance of medical image segmentation is increasingly defined by the efficiency of data utilization rather than merely the volume of raw data. Accurate segmentation, partic…

cs.CV2025

Mammo-Clustering: A Multi-views Tri-level Information Fusion Context Clustering Framework for Localization and Classification in Mammography

Shilong Yang, Chulong Zhang, Qi Zang +8

Breast cancer is a significant global health issue, and the diagnosis of breast imaging has always been challenging. Mammography images typically have extremely high resolution, wi…

eess.SY2020

Incorporating Gas Pipeline Leakage Failure Modes in Risk Evaluation of Electricity-Gas Integrated Energy Systems

Yi Tang, Yuan Zhao, Wenyuan Li +2

In the existing literatures for the risk evaluation of electricity-gas integrated energy system (EGIES), the impacts of gas leakage in pipelines are ignored. This paper presents a…

eess.SP2019

Fast Calculation of Probabilistic Optimal Power Flow: A Deep Learning Approach

Yan Yang, Juan Yu, Zhifang Yang +2

Probabilistic optimal power flow (POPF) is an important analytical tool to ensure the secure and economic operation of power systems. POPF needs to solve enormous nonlinear and non…

cond-mat.str-el2010

Possible link of a structurally driven spin flip transition and the insulator-metal transition in the perovskite LaBaCoO

Peng Tong, Juan Yu, Qingzhen Huang +2

The complex nature of the magnetic ground state in LaACoO (A = Ca, Sr, Ba) has been investigated via neutron scattering. It was previously observed that ferroma…