Qianxiao Li

National University of Singapore — Singapore

Physics and Astronomy · Physical Sciences

22h-index2.4kcitations137works3.12yr avg
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Research Topics

Model Reduction and Neural Networks(38), Machine Learning in Materials Science(24), Neural Networks and Applications(22), Stochastic Gradient Optimization Techniques(11), Adversarial Robustness in Machine Learning(10)

Publications137 total

AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions
arXiv (Cornell University)·2025Open Access
Scalable learning of macroscopic stochastic dynamics
arXiv (Cornell University)·2025Open Access
On the Universal Approximation Property of Deep Fully Convolutional Neural Networks
SIAM Journal on Mathematical Analysis·2025
Learning task-specific predictive models for scientific computing
arXiv (Cornell University)·2025Open Access
Mitigating Distribution Shift in Machine Learning–Augmented Hybrid Simulation
SIAM Journal on Scientific Computing·2025· 1 cited
Learning Parametric Koopman Decompositions for Prediction and Control
SIAM Journal on Applied Dynamical Systems·2025· 1 cited
Learning Dynamics of Nonlinear Field‐Circuit Coupled Problems With a Physics‐Data Combined Model
International Journal for Numerical Methods in Engineering·2025· 2 citedOpen Access
Interpolation, Approximation, and Controllability of Deep Neural Networks
SIAM Journal on Control and Optimization·2025· 7 cited
An Optimal Control View of LoRA and Binary Controller Design for Vision Transformers
Lecture notes in computer science·2024
Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models
arXiv (Cornell University)·2024Open Access
Learning Macroscopic Dynamics from Partial Microscopic Observations
arXiv (Cornell University)·2024Open Access
Author response for "Multi-Objective Synthesis Optimization and Kinetics of a Sustainable Terpolymer"
2024
Multi-Objective Synthesis Optimization and Kinetics of a Sustainable Terpolymer
2024· 2 citedOpen Access
DynGMA: A robust approach for learning stochastic differential equations from data
Journal of Computational Physics·2024· 1 cited
Evolution-guided Bayesian optimization for constrained multi-objective optimization in self-driving labs
npj Computational Materials·2024· 53 citedOpen Access
Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving
arXiv (Cornell University)·2024· 1 citedOpen Access
From Generalization Analysis to Optimization Designs for State Space Models
arXiv (Cornell University)·2024Open Access
Non-intrusive model combination for learning dynamical systems
Physica D Nonlinear Phenomena·2024· 2 cited
PID Control-Based Self-Healing to Improve the Robustness of Large Language Models
arXiv (Cornell University)·2024Open Access
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms
SIAM Journal on Scientific Computing·2024· 6 cited
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Frequent Co-authors

Tonio Buonassisi(12), E Weinan(11), Zekun Ren(10), Kedar Hippalgaonkar(10), Siyu Tian(9), Cheng Tai(8), J. Senthilnath(6), Flore Mekki‐Berrada(5), Daniil Bash(5), Xiaonan Wang(5), Felipe Oviedo(5), Armin G. Aberle(5), Jatin Kumar(5), Zuowei Shen(5), Felix Dietrich(4), Ioannis G. Kevrekidis(4), Wai Kuan Wong(4), Jiaxun Xie(4), Saif A. Khan(4), Yee‐Fun Lim(4)