Wei Liu

Finance · with Röckner · 2008–2021

A researcher in the Science corpus: 9 papers; trusts 41 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Finance — 75 citations into it; #942 of 10,518 by trust here, #3,592 by citations
• Applied Mathematics — 44 citations into it; #1,696 of 7,620 by trust here, #3,589 by citations
• Computational Theory and Mathematics — 42 citations into it; #904 of 12,182 by trust here, #4,531 by citations
• Control and Systems Engineering — 24 citations into it; #3,094 of 8,257 by trust here, #5,784 by citations
• Mathematical Physics — 21 citations into it; #629 of 8,562 by trust here, #2,288 by citations
• Computational Mechanics — 14 citations into it; #4,397 of 10,001 by trust here, #9,276 by citations
• Numerical Analysis — 13 citations into it
• Management Science and Operations Research — 6 citations into it

Whom Wei Liu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Michael Röckner
2. Feng-Yu Wang
3. Jiagang Ren
4. Claudia Prévôt
5. Wei David Liu
6. Benjamin Gess
7. István Gyöngy
8. Francis Comets
9. Xicheng Zhang
10. Zdzisław Brzeźniak

Who trusts Wei Liu overall

1. Michael Röckner
2. Xicheng Zhang
3. Tusheng Zhang
4. A. Budhiraja
5. Shijie Shang
6. Zdzisław Brzeźniak
7. Wei David Liu
8. Igor D. Chueshov
9. Benjamin Gess
10. Anis Matoussi

Papers from Wei Liu's perspective

Ordered by how strongly the researchers Wei Liu trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. A Concise Course on Stochastic Partial Differential Equations
4. Gradient-based learning applied to document recognition
5. Large Deviations for Stochastic Evolution Equations with Small Multiplicative Noise
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• Large Deviations for Stochastic Evolution Equations with Small Multiplicative Noise (2008) — 142 citations
• SPDE in Hilbert space with locally monotone coefficients (2010) — 208 citations
• Strong convergence rates in averaging principle for slow-fast McKean-Vlasov SPDEs (2021) — 62 citations
• Averaging principle for slow-fast stochastic differential equations with time dependent locally Lipschitz coefficients (2018) — 123 citations
• The partially truncated Euler–Maruyama method and its stability and boundedness (2017) — 61 citations
• Stochastic Partial Differential Equations: An Introduction (2015) — 568 citations
• Well-posedness of stochastic partial differential equations with Lyapunov condition (2013) — 62 citations
• Local and global well-posedness of SPDE with generalized coercivity conditions☆ (2012) — 119 citations
• Harnack inequality and applications for stochastic evolution equations with monotone drifts (2008) — 85 citations