Qian Li
Cellular and Molecular Neuroscience · with Zhong · 2016–2023
A researcher in the Science corpus: 11 papers; trusts 113 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Cellular and Molecular Neuroscience — 174 citations into it; #1,193 of 2,998 by trust here, #1,779 by citations
- Artificial Intelligence — 107 citations into it; #22,640 of 35,345 by trust here, #16,471 by citations
- Computer Vision and Pattern Recognition — 89 citations into it; #15,985 of 21,575 by trust here, #12,419 by citations
- Cognitive Neuroscience — 57 citations into it; #10,239 of 10,852 by trust here, #6,526 by citations
- Genetics — 55 citations into it
- Meta & Continual Learning — 55 citations into it; #720 of 1,041 by trust here, #606 by citations
- Molecular Biology — 49 citations into it
- Representation & Self-Supervised Learning — 49 citations into it
Whom Qian Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Yichun Shuai
- Geoffrey E. Hinton
- Ronald L. Davis
- Jacob A. Berry
- Kaiming He
- Yoshua Bengio
- Yann LeCun
- Diederik P. Kingma
- Seyed Iman Mirzadeh
Who trusts Qian Li overall
Papers from Qian Li's perspective
Ordered by how strongly the researchers Qian Li trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- AFEC: Active Forgetting of Negative Transfer in Continual Learning (2021) — 123 citations
- Cdc42-Dependent Forgetting Regulates Repetition Effect in Prolonging Memory Retention. (2016) — 43 citations
- Differential conditioning produces merged long-term memory in Drosophila (2021) — 9 citations
- Spontaneous recovery of reward memory through active forgetting of extinction memory. (2023) — 17 citations
- Incorporating neuro-inspired adaptability for continual learning in artificial intelligence (2023) — 101 citations
- Genetic dissection of mutual interference between two consecutive learning tasks in Drosophila (2022) — 3 citations
- CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One (2022) — 78 citations
- Age‐related memory vulnerability to interfering stimuli is caused by gradual loss of MAPK‐dependent protection in Drosophila (2022) — 8 citations
- Triple-Memory Networks: A Brain-Inspired Method for Continual Learning (2020) — 64 citations
- Genetic dissection of active forgetting in labile and consolidated memories in Drosophila (2019) — 33 citations
- Active Protection: Learning-Activated Raf/MAPK Activity Protects Labile Memory from Rac1-Independent Forgetting. (2018) — 47 citations