activity
20132026
most citedThe mixed geominimal surface areas for multiple convex bodies

31 citations · 51 across the 12 of their papers we have counts for

collaborators

13 papers

math.MG2026

The Minkowski problem for -close sets: existence and continuity

Wen Ai, Deping Ye, Baocheng Zhu

Let be a pointed closed convex cone in with nonempty interior, and let denote the unit sphere in . The Minkowski problem for -cl…

math.MG2026

A Minkowski Theory for the Exterior Capacitary Volumes and A Resolution of the Pólya-Szegö Conjecture

Qiushuang Liu, Jie Xiao, Ning Zhang +2

This paper establishes a unified Minkowski theory for exterior p-capacitary volumes and resolves the classical Pólya-Szegö conjecture on the electrostatic capacity of convex bodies…

math.MG2024

Asymptotic theory of -pseudo-cones

Xudong Wang, Wenxue Xu, Jiazu Zhou +1

In this paper, we study the non-degenerated -pseudo-cones which can be uniquely decomposed into the sum of a -asymptotic set and a -starting point. Combining this with the…

math.MG2022★ 12 cited

On the Brunn-Minkowski theory and the Minkowski problem for -coconvex sets

Jin Yang, Deping Ye, Baocheng Zhu

Let be a pointed closed convex cone in with vertex at the origin and having nonempty interior. The set is -coconvex if the volume of is f…

math.MG2021★ 1 cited

On the Musielak-Orlicz-Gauss image problem

Qingzhong Huang, Sudan Xing, Deping Ye +1

In the present paper we initiate the study of the Musielak-Orlicz-Brunn-Minkowski theory for convex bodies. In particular, we develop the Musielak-Orlicz-Gauss image problem aiming…

cs.LG2020★ 1 cited

Neural Physicist: Learning Physical Dynamics from Image Sequences

Baocheng Zhu, Shijun Wang, James Zhang

We present a novel architecture named Neural Physicist (NeurPhy) to learn physical dynamics directly from image sequences using deep neural networks. For any physical system, given…

cs.LG2020

Riemannian Proximal Policy Optimization

Shijun Wang, Baocheng Zhu, Chen Li +4

In this paper, We propose a general Riemannian proximal optimization algorithm with guaranteed convergence to solve Markov decision process (MDP) problems. To model policy function…

cs.LG2020★ 1 cited

A Riemannian Primal-dual Algorithm Based on Proximal Operator and its Application in Metric Learning

Shijun Wang, Baocheng Zhu, Lintao Ma +1

In this paper, we consider optimizing a smooth, convex, lower semicontinuous function in Riemannian space with constraints. To solve the problem, we first convert it to a dual prob…

math.MG2019

The general dual-polar Orlicz-Minkowski problem

Sudan Xing, Deping Ye, Baocheng Zhu

This paper gives a systematic study to the general dual-polar Orlicz-Minkowski problem (e.g., Problem \ref{general-dual-polar}). This problem involves the general dual volume $\wid…

math.MG2018★ 4 cited

On the polar Orlicz-Minkowski problems and the -capacitary Orlicz-Petty bodies

Xiaokang Luo, Deping Ye, Baocheng Zhu

In this paper, we propose and study the polar Orlicz-Minkowski problems: under what conditions on a nonzero finite measure and a continuous function $φ:(0,\infty)\rightarrow(0,…

math.MG2017★ 1 cited

The dual Orlicz-Minkowski problem

Baocheng Zhu, Sudan Xing, Deping Ye

In this paper, the dual Orlicz curvature measure is proposed and its basic properties are provided. A variational formula for the dual Orlicz-quermassintegral is established in ord…

math.MG2016

The Orlicz-Petty bodies

Baocheng Zhu, Han Hong, Deping Ye

This paper is dedicated to the Orlicz-Petty bodies. We first propose the homogeneous Orlicz affine and geominimal surface areas, and establish their basic properties such as homoge…

math.MG2013★ 31 cited

The mixed geominimal surface areas for multiple convex bodies

Deping Ye, Baocheng Zhu, Jiazu Zhou

In this paper, we introduce several mixed geominimal surface areas for multiple convex bodies for all . Our definitions are motivated from an equivalent formula for…