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researcher

Junyu Liu

57 papers hereh-index 283k citations74 works total

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

author position
  • sole author3
  • first author16
  • middle author24
  • last author14

Across the 57 of 57 papers where every author was matched, so the position is known.

fields
  • hep-th27
  • quant-ph22
  • cs.LG4
  • astro-ph.CO1
  • gr-qc1
  • math.AP1
same name
  • Junyu Liu — 30 papers, h 9
  • Junyu Liu — 18 papers, h 25
  • Junyu Liu — 12 papers, h 5
  • Junyu Liu — 11 papers, h 3
  • Junyu Liu — 10 papers, h 4
  • Junyu Liu — 8 papers, h 4

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
20152023
most citedQuantum Simulation for High Energy Physics

332 citations · 2.8k across the 55 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023★ 13 cited

Beyond MD17: the reactive xxMD dataset

Zihan Pengmei, Junyu Liu, Yinan Shu

System specific neural force fields (NFFs) have gained popularity in computational chemistry. One of the most popular datasets as a bencharmk to develop NFFs models is the MD17 dat…

cs.LG2023

Catapult Dynamics and Phase Transitions in Quadratic Nets

David Meltzer, Min Chen, Junyu Liu

Neural networks trained with gradient descent can undergo non-trivial phase transitions as a function of the learning rate. In \cite{lewkowycz2020large} it was discovered that wide…

cs.LG2022★ 3 cited

Unifying O(3) Equivariant Neural Networks Design with Tensor-Network Formalism

Zimu Li, Zihan Pengmei, Han Zheng +3

Many learning tasks, including learning potential energy surfaces from ab initio calculations, involve global spatial symmetries and permutational symmetry between atoms or general…

cs.LG2022★ 10 cited

Laziness, Barren Plateau, and Noise in Machine Learning

Junyu Liu, Zexi Lin, Liang Jiang

We define \emph{laziness} to describe a large suppression of variational parameter updates for neural networks, classical or quantum. In the quantum case, the suppression is expone…

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