Yanzhao Cao - RankMe

54 papers B 1Misc 1Journal 51Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Error estimates of a training-free diffusion model for high-dimensional sampling. CoRR Pengjun Wang, Zezhong Zhang, Minglei Yang, Feng Bao, Yanzhao Cao, Guannan Zhang
2026	J	`jnl`	Generative AI models for learning flow maps of stochastic dynamical systems in bounded domains. J. Comput. Phys. Minglei Yang, Yanfang Liu, Diego del-Castillo-Negrete, Yanzhao Cao, Guannan Zhang
2026	J	`jnl`	Learning non-separable Hamiltonian systems with pseudo-symplectic neural network. J. Comput. Phys. Xupeng Cheng, Lijin Wang, Yanzhao Cao, Chen Chen
2026	J	`jnl`	Weak Convergence of Drift-Implicit Euler and Spectral Galerkin Approximation to Stochastic Allen-Cahn Equation Driven by Multiplicative Trace-Class Noise. J. Sci. Comput. Minxing Zhang, Yongkui Zou, Ran Zhang, Yanzhao Cao
2025	J	`jnl`	Generative AI Models for Learning Flow Maps of Stochastic Dynamical Systems in Bounded Domains. CoRR Minglei Yang, Yanfang Liu, Diego del-Castillo-Negrete, Yanzhao Cao, Guannan Zhang
2025	J	`jnl`	Learning Hamiltonian Systems with Pseudo-symplectic Neural Network. CoRR Xupeng Cheng, Lijin Wang, Yanzhao Cao, Chen Chen
2025	J	`jnl`	Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network. CoRR Chen Chen, Lijin Wang, Yanzhao Cao, Xupeng Cheng
2025	J	`jnl`	Numerical approximations for partially observed optimal control of stochastic partial differential equations. CoRR Feng Bao, Yanzhao Cao, Hongjiang Qian
2025	J	`jnl`	Splitting Finite Element Approximations for Quasi-Static Electroporoelasticity Equations. J. Sci. Comput. Xuan Liu, Yongkui Zou, Ran Zhang, Yanzhao Cao, Amnon J. Meir
2025	J	`jnl`	Splitting finite element approximations for quasi-static electroporoelasticity equations. CoRR Xuan Liu, Yongkui Zou, Ran Zhang, Yanzhao Cao, Amnon J. Meir
2025	B	`conf`	TF-Diff: Training-free Diffusion for Cross-Domain RF-based Human Activity Recognition. GLOBECOM Ziqi Wang, Shiwen Mao, Feng Bao, Yanzhao Cao
2025	J	`jnl`	Weak Convergence Analysis for the Finite Element Approximation to Stochastic Allen-Cahn Equation Driven by Multiplicative White Noise. CoRR Minxing Zhang, Yongkui Zou, Ran Zhang, Yanzhao Cao
2024	J	`jnl`	A Pseudoreversible Normalizing Flow for Stochastic Dynamical Systems with Various Initial Distributions. SIAM J. Sci. Comput. Minglei Yang, Pengjun Wang, Diego del-Castillo-Negrete, Yanzhao Cao, Guannan Zhang
2024	J	`jnl`	Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation. CoRR Minglei Yang, Pengjun Wang, Ming Fan, Dan Lu, Yanzhao Cao, Guannan Zhang
2024	J	`jnl`	Numerical Analysis for Convergence of a Sample-Wise Backpropagation Method for Training Stochastic Neural Networks. SIAM J. Numer. Anal. Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun
2024	J	`jnl`	Numerical analysis of a time discretized method for nonlinear filtering problem with Lévy process observations. Adv. Comput. Math. Fengshan Zhang, Yongkui Zou, Shimin Chai, Yanzhao Cao
2024	J	`jnl`	Strong convergence of an explicit full-discrete scheme for stochastic Burgers-Huxley equation. CoRR Yibo Wang, Wanrong Cao, Yanzhao Cao
2023	J	`jnl`	A Probabilistic Scheme for Semilinear Nonlocal Diffusion Equations with Volume Constraints. SIAM J. Numer. Anal. Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete, Yanzhao Cao
2023	J	`jnl`	A pseudo-reversible normalizing flow for stochastic dynamical systems with various initial distributions. CoRR Minglei Yang, Pengjun Wang, Diego del-Castillo-Negrete, Yanzhao Cao, Guannan Zhang
2023	J	`jnl`	Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation. CoRR Yanfang Liu, Minglei Yang, Zezhong Zhang, Feng Bao, Yanzhao Cao, Guannan Zhang
2023	J	`jnl`	Fast and Accuracy-Preserving Domain Decomposition Methods for Reduced Fracture Models with Nonconforming Time Grids. J. Sci. Comput. Phuoc-Toan Huynh, Yanzhao Cao, Thi-Thao-Phuong Hoang
2023	J	`jnl`	Splitting scheme for backward doubly stochastic differential equations. Adv. Comput. Math. Feng Bao, Yanzhao Cao, He Zhang
2022	J	`jnl`	A probabilistic scheme for semilinear nonlocal diffusion equations with volume constraints. CoRR Minglei Yang, Guannan Zhang, Diego del-Castillo-Negrete, Yanzhao Cao
2022	J	`jnl`	Convergence Analysis for Training Stochastic Neural Networks via Stochastic Gradient Descent. CoRR Richard Archibald, Feng Bao, Yanzhao Cao, Hui Sun
2022	J	`jnl`	Fast and accurate domain decomposition methods for reduced fracture models with nonconforming time grids. CoRR Phuoc-Toan Huynh, Yanzhao Cao, Thi-Thao-Phuong Hoang
2022	J	`jnl`	Numerical analysis of a time discretized method for nonlinear filtering problem with Lévy process observations. CoRR Fengshan Zhang, Yongkui Zou, Shimin Chai, Yanzhao Cao
2022	J	`jnl`	Splitting-up Spectral Method for Nonlinear Filtering Problems with Correlation Noises. J. Sci. Comput. Fengshan Zhang, Yongkui Zou, Shimin Chai, Ran Zhang, Yanzhao Cao
2021	J	`jnl`	Adaptive Gradient Descent for Optimal Control of Parabolic Equations with Random Parameters. CoRR Yanzhao Cao, Somak Das, Hans-Werner van Wyk
2021	J	`jnl`	Mean-square convergence of numerical methods for random ordinary differential equations. Numer. Algorithms Peng Wang, Yanzhao Cao, Xiaoying Han, Peter Kloeden
2021	J	`jnl`	Solving Backward Doubly Stochastic Differential Equations through Splitting Schemes. CoRR Feng Bao, Yanzhao Cao, He Zhang
2020	J	`jnl`	A locking free numerical approximation for quasilinear poroelasticity problems. Comput. Math. Appl. Jingyuan Zhang, Chenguang Zhou, Yanzhao Cao, Amnon J. Meir
2020	J	`jnl`	Analysis of the Stochastic Alternating Least Squares Method for the Decomposition of Random Tensors. CoRR Yanzhao Cao, Somak Das, Luke Oeding, Hans-Werner van Wyk
2020	J	`jnl`	Uncertainty Quantification in Deep Learning through Stochastic Maximum Principle. CoRR Richard Archibald, Feng Bao, Yanzhao Cao, He Zhang
2019	J	`jnl`	An explicit a posteriori error estimations for the cell functional minimization scheme of elliptic problems. J. Comput. Appl. Math. Li Yin, Zhiming Gao, Yanzhao Cao
2018	J	`jnl`	A Robust Numerical Method for the Random Interface Grating Problem via Shape Calculus, Weak Galerkin Method, and Low-Rank Approximation. J. Sci. Comput. Gang Bao, Yanzhao Cao, Yongle Hao, Kai Zhang
2017	J	`jnl`	A fast discrete spectral method for stochastic partial differential equations. Adv. Comput. Math. Yanzhao Cao, Ying Jiang, Yuesheng Xu
2017	J	`jnl`	Approximating Stochastic Evolution Equations with Additive White and Rough Noises. SIAM J. Numer. Anal. Yanzhao Cao, Jialin Hong, Zhihui Liu
2017	J	`jnl`	Computational singular perturbation analysis of stochastic chemical systems with stiffness. J. Comput. Phys. Lijin Wang, Xiaoying Han, Yanzhao Cao, Habib N. Najm
2016	J	`jnl`	A First Order Scheme for Backward Doubly Stochastic Differential Equations. SIAM/ASA J. Uncertain. Quantification Feng Bao, Yanzhao Cao, Amnon J. Meir, Weidong Zhao
2016	Misc	`conf`	Particle Swarm Optimization Simulation via Optimal Halton Sequences. ICCS Ganesha Weerasinghe, Hongmei Chi, Yanzhao Cao
2016	J	`jnl`	Well-posedness and a numerical study of a regularization model with adaptive nonlinear filtering for incompressible fluid flow. Comput. Math. Appl. Yanzhao Cao, Song Chen, Leo G. Rebholz
2014	J	`jnl`	A Hybrid Sparse-Grid Approach for Nonlinear Filtering Problems Based on Adaptive-Domain of the Zakai Equation Approximations. SIAM/ASA J. Uncertain. Quantification Feng Bao, Yanzhao Cao, Clayton G. Webster, Guannan Zhang
2014	J	`jnl`	Orthogonal polynomial expansions on sparse grids. J. Complex. Yanzhao Cao, Ying Jiang, Yuesheng Xu
2014	J	`jnl`	Parallel, non-iterative, multi-physics domain decomposition methods for time-dependent Stokes-Darcy systems. Math. Comput. Yanzhao Cao, Max D. Gunzburger, Xiaoming He, Xiaoming Wang
2011	J	`jnl`	Robin-Robin domain decomposition methods for the steady-state Stokes-Darcy system with the Beavers-Joseph interface condition. Numerische Mathematik Yanzhao Cao, Max D. Gunzburger, Xiaoming He, Xiaoming Wang
2010	J	`jnl`	Error analysis of finite element approximations of the stochastic Stokes equations. Adv. Comput. Math. Yanzhao Cao, Zheng Chen, Max D. Gunzburger
2010	J	`jnl`	Finite Element Approximations for Stokes-Darcy Flow with Beavers-Joseph Interface Conditions. SIAM J. Numer. Anal. Yanzhao Cao, Max D. Gunzburger, Xiaolong Hu, Fei Hua, Xiaoming Wang, Weidong Zhao
2010	—	`conf`	Generating Parallel Random Sequences via Parameterizing EICGs for Heterogeneous Computing Environments. ICCSA (4) Hongmei Chi, Yanzhao Cao
2009	J	`jnl`	A Fast Collocation Method for Solving Stochastic Integral Equations. SIAM J. Numer. Anal. Yanzhao Cao, Bin Wu, Yuesheng Xu
2008	J	`jnl`	Exploitation of sensitivity derivatives via randomized quasi-Monte Carlo methods. Monte Carlo Methods Appl. Yanzhao Cao, Hongmei Chi, C. Milton, Weidong Zhao
2007	J	`jnl`	Finite element methods for semilinear elliptic stochastic partial differential equations. Numerische Mathematik Yanzhao Cao, Hongtao Yang, Li Yin
2003	J	`jnl`	A Hybrid Collocation Method for Volterra Integral Equations with Weakly Singular Kernels. SIAM J. Numer. Anal. Yanzhao Cao, Terry Herdman, Yuesheng Xu
2003	J	`jnl`	An Efficient Monte Carlo Method for Optimal Control Problems with Uncertainty. Comput. Optim. Appl. Yanzhao Cao, M. Yousuff Hussaini, Thomas A. Zang
2001	J	`jnl`	Numerical approximations of exact controllability problems by optimal control problems for parabolic differential equations. Appl. Math. Comput. Yanzhao Cao

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.