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Kailiang Wu

39 papers hereh-index 221.6k citations56 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author3
  • first author18
  • middle author7
  • last author11

Across the 39 of 39 papers where every author was matched, so the position is known.

fields
  • math.NA35
  • cs.LG4
same name
  • Kailiang Wu — 17 papers, h 6
  • Kailiang Wu — 10 papers, h 2
  • Kailiang Wu — 3 papers, h 2
  • Kailiang Wu — 2 papers, h 2
  • Kailiang Wu — 1 paper, h 3
  • Kailiang Wu — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152024
most citedData Driven Governing Equations Approximation Using Deep Neural Networks

293 citations · 1.2k across the 39 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023★ 1 cited

Critical Sampling for Robust Evolution Operator Learning of Unknown Dynamical Systems

Ce Zhang, Kailiang Wu, Zhihai He

Given an unknown dynamical system, what is the minimum number of samples needed for effective learning of its governing laws and accurate prediction of its future evolution behavio…

cs.LG2023★ 1 cited

Deep-OSG: Deep Learning of Operators in Semigroup

Junfeng Chen, Kailiang Wu

This paper proposes a novel deep learning approach for learning operators in semigroup, with applications to modeling unknown autonomous dynamical systems using time series data co…

cs.LG2021★ 4 cited

Deep Neural Network Modeling of Unknown Partial Differential Equations in Nodal Space

Zhen Chen, Victor Churchill, Kailiang Wu +1

We present a numerical framework for deep neural network (DNN) modeling of unknown time-dependent partial differential equations (PDE) using their trajectory data. Unlike the recen…

cs.LG2020

A Non-Intrusive Correction Algorithm for Classification Problems with Corrupted Data

Jun Hou, Tong Qin, Kailiang Wu +1

A novel correction algorithm is proposed for multi-class classification problems with corrupted training data. The algorithm is non-intrusive, in the sense that it post-processes a…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.