Yiping Lu
15 papers · 2018–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (26) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Topic Evolution
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Keyword Collector
(75)
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Trend Setter
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Century Club Β· Bronze
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Research topics
Machine Learning
(12)
Optimization & Theory Β· Machine Learning
(10)
Deep Learning
(7)
Architectures
(4)
Mathematics & Optimization
(3)
Core Methods
(3)
Learning Types Β· Machine Learning
(3)
Mathematics
(3)
Optimization & Theory Β· Deep Learning
(3)
Artificial Intelligence
(2)
Core AI
(2)
Learning Types Β· Deep Learning
(2)
Optimization
(2)
Techniques
(2)
Computer Vision
(1)
Keywords
neural network
(5)
partial differential equation
(3)
generalization bound
(2)
minimax optimality
(2)
physics-informed neural network
(2)
monte carlo simulation
(1)
global convergence
(1)
adversarial robustness
(1)
iterative sketching
(1)
neural network optimization
(1)
computational efficiency
(1)
iterative refinement
(1)
kl divergence
(1)
reproducing kernel hilbert space
(1)
stochastic control
(1)
adversarial training
(1)
gradient descent
(1)
nonparametric regression
(1)
nonparametric estimation
(1)
system identification
(1)
Papers
Randomized Iterative Solver as Iterative Refinement: A Simple Fix Towards Backward Stability
AISTATS 2025
Generalization of Scaled Deep ResNets in the Mean-Field Regime
ICLR 2024
Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
ICML 2024
Statistical Spatially Inhomogeneous Diffusion Inference
AAAI 2024
Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
AISTATS 2023
Minimax Optimal Kernel Operator Learning via Multilevel Training
ICLR 2023
When can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality
NeurIPS 2023
An Unconstrained Layer-Peeled Perspective on Neural Collapse
ICLR 2022
Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality
ICLR 2022
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent
NeurIPS 2022
A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth
ICML 2020
Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration
ICLR 2019
You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle
NeurIPS 2019
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
ICML 2018
PDE-Net: Learning PDEs from Data
ICML 2018