Kailai Xu

18 papers Journal 14Unranked 4

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	Physics constrained learning for data-driven inverse modeling from sparse observations. J. Comput. Phys. Kailai Xu, Eric Darve
2021	J	`jnl`	A general approach to seismic inversion with automatic differentiation. Comput. Geosci. Weiqiang Zhu, Kailai Xu, Eric Darve, Gregory C. Beroza
2021	—	`conf`	ADCME MPI: Distributed Machine Learning for Computational Engineering. AAAI Spring Symposium: MLPS Kailai Xu, Eric Darve
2021	J	`jnl`	Learning constitutive relations using symmetric positive definite neural networks. J. Comput. Phys. Kailai Xu, Daniel Zhengyu Huang, Eric Darve
2021	J	`jnl`	Trust Region Method for Coupled Systems of PDE Solvers and Deep Neural Networks. CoRR Kailai Xu, Eric Darve
2020	J	`jnl`	ADCME: Learning Spatially-varying Physical Fields using Deep Neural Networks. CoRR Kailai Xu, Eric Darve
2020	—	`conf`	Calibrating Multivariate Lévy Processes with Neural Networks. MSML Kailai Xu, Eric Darve
2020	—	`conf`	Data-Driven Inverse Modeling with Incomplete Observations. AAAI Spring Symposium: MLPS Kailai Xu, Eric Darve
2020	J	`jnl`	Distributed Machine Learning for Computational Engineering using MPI. CoRR Kailai Xu, Weiqiang Zhu, Eric Darve
2020	J	`jnl`	Inverse Modeling of Viscoelasticity Materials using Physics Constrained Learning. CoRR Kailai Xu, Alexandre M. Tartakovsky, Jeff Burghardt, Eric Darve
2020	J	`jnl`	Learning Constitutive Relations using Symmetric Positive Definite Neural Networks. CoRR Kailai Xu, Daniel Zhengyu Huang, Eric Darve
2020	J	`jnl`	Learning constitutive relations from indirect observations using deep neural networks. J. Comput. Phys. Daniel Zhengyu Huang, Kailai Xu, Charbel Farhat, Eric Darve
2020	J	`jnl`	Physics Constrained Learning for Data-driven Inverse Modeling from Sparse Observations. CoRR Kailai Xu, Eric Darve
2020	J	`jnl`	Solving Inverse Problems in Steady State Navier-Stokes Equations using Deep Neural Networks. CoRR Tiffany Fan, Kailai Xu, Jay Pathak, Eric Darve
2019	J	`jnl`	Adversarial Numerical Analysis for Inverse Problems. CoRR Kailai Xu, Eric Darve
2019	J	`jnl`	Learning Hidden Dynamics using Intelligent Automatic Differentiation. CoRR Kailai Xu, Dongzhuo Li, Eric Darve, Jerry M. Harris
2018	J	`jnl`	Calibrating Lévy Process from Observations Based on Neural Networks and Automatic Differentiation with Convergence Proofs. CoRR Kailai Xu, Eric Darve
2010	—	`conf`	Study on Stability of Vehicle Mass Analysis System. ISIA Wei Shi, Shusheng Xiong, Chaoshan Zhang, Yaohua Jiang, Wei Li, Xijiang Wu, Xiaoshuai Ren, Wenhua He, Kailai Xu, Ji Zhou

2025 Best paper conf

Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja.

CheckMATE

Nicolò Altamura, Enrico Bragastini, Marco Campion, Mila Dalla Preda

2026 Best paper preprint

ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage.

arXiv

Chang Liu, Noah Fleischmann, Nicolò Altamura, Edward Raff, James Holt, Kristopher Micinski