Qi Liu
Artificial Intelligence · Neural Information Processing Systems · 2008–2023
A researcher in the Science corpus: 31 papers; trusts 695 researchers and is trusted by 44 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 539 citations into it; #6,269 of 35,345 by trust here, #4,682 by citations
- Computer Vision and Pattern Recognition — 239 citations into it; #6,903 of 21,575 by trust here, #7,092 by citations
- Natural Language Processing — 150 citations into it; #1,710 of 5,688 by trust here, #2,955 by citations
- Information Systems — 117 citations into it
- Molecular Biology — 101 citations into it; #5,562 of 17,773 by trust here, #7,124 by citations
- Representation & Self-Supervised Learning — 91 citations into it; #1,535 of 3,145 by trust here, #2,624 by citations
- Graph Learning — 73 citations into it
- Model Architectures — 72 citations into it
Whom Qi Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Alex Graves
- Kaiming He
- Jimmy Ba
- Sepp Hochreiter
Who trusts Qi Liu overall
- Ines Chami
- Yu Zhang
- Qiang Yang
- Shitong Luo
- Wengong Jin
- William Chan
- Ying Luo
- Hang Yan
- Chengxi Zang
- Ming Tu
Papers from Qi Liu's perspective
Ordered by how strongly the researchers Qi Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Insertion-based Decoding with Automatically Inferred Generation Order (2019) — 122 citations
- Hyperbolic Graph Neural Networks (2019) — 499 citations
- Quaternion Knowledge Graph Embeddings (2019) — 583 citations
- Incremental semi-supervised learning on streaming data (2019) — 58 citations
- Sentence-State LSTM for Text Representation (2018) — 225 citations
- Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples (2018) — 336 citations
- Constrained Graph Variational Autoencoders for Molecule Design (2018) — 513 citations
- Transfer across Completely Different Feature Spaces via Spectral Embedding (2013) — 63 citations
- Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective (2019) — 228 citations
- HIT: linking herbal active ingredients to targets (2010) — 301 citations
- Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study (2010) — 85 citations
- Fusion of Magnetic and Visual Sensors for Indoor Localization: Infrastructure-Free and More Effective (2017) — 114 citations
- Neural Mathematical Solver with Enhanced Formula Structure (2020) — 29 citations
- An improved method to construct basic probability assignment based on the confusion matrix for classification problem (2016) — 559 citations
- When large language models meet personalization: perspectives of challenges and opportunities (2023) — 347 citations
- A survey on large language models for recommendation (2023) — 899 citations
- In-sensor reservoir computing system for latent fingerprint recognition with deep ultraviolet photo-synapses and memristor array (2022) — 309 citations
- Motif-based Graph Self-Supervised Learning for Molecular Property Prediction (2021) — 370 citations
- HMS: A Hierarchical Solver with Dependency-Enhanced Understanding for Math Word Problem (2021) — 72 citations
- DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesis (2021) — 128 citations