深度学习领域综述总结汇总
Contents
深度学习领域综述总结汇总#
2019-2020#
序号 |
名称 |
说明 |
备注 |
---|---|---|---|
1 |
A guide to deep learning in healthcare |
医疗深度学习技术指南 |
|
2 |
Multimodal Machine Learning: A Survey and Taxonomy |
多模态机器学习 |
|
3 |
Few-shot Learning: A Survey |
小样本 |
|
4 |
Meta-Learning A Survey |
元学习 |
|
5 |
Multimodal Intelligence: Representation Learning, Information Fusion, and Applications |
迁移学习 |
|
6 |
Multimodal Intelligence Representation Learning,Information Fusion, and Applications |
多模态 |
|
7 |
Object Detection in 20 Years: A Survey |
目标检测 |
|
8 |
A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications |
汉语知识图构建技术及其应用综述 |
|
9 |
Advances and Open Problems in Federated Learning |
联邦学习 |
|
10 |
Optimization for deep learning theory and algorithms |
深度学习优化理论算法 |
2020-2021#
序号 |
名称 |
说明 |
备注 |
---|---|---|---|
1 |
Recent advances in deep learning theory |
深度学习理论 |
|
2 |
Learning from Very Few Samples: A Survey |
少样本学习 |
|
3 |
A Survey on Knowledge Graphs: Representation, Acquisition and Applications |
知识图谱研究 |
|
4 |
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications |
GAN算法理论和应用 |
|
5 |
A Survey on Causal Inference |
因果推断综述论文 |
|
6 |
Pre-trained Models for Natural Language Processing: A Survey |
自然语言处理的预训练模型 |
|
7 |
A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources |
异质图嵌入 |
|
8 |
Graph Neural Networks: Taxonomy, Advances and Trends |
图神经网络 |
|
9 |
Efficient Transformers: A Survey |
高效Transformer |
|
10 |
Self-supervised Learning: Generative or Contrastive |
自我监督学习 |
2021-2022#
序号 |
名称 |
说明 |
备注 |
---|---|---|---|
1 |
关于深度学习的一点思考 |
深度学习 |
周志华 |
2 |
Attention Mechanisms in Computer Vision: A Survey |
注意力机制 |
|
3 |
Geometric Deep Learning Grids, Groups, Graphs, Geodesics, and Gauges |
几何深度学习 |
|
4 |
A Survey of Transformers |
Transformer |
|
5 |
Model Complexity of Deep Learning: A Survey |
深度学习模型复杂性 |
|
6 |
Towards Out-Of-Distribution Generalization: A Survey |
分布外泛化 |
|
7 |
Deep Long-Tailed Learning: A Survey |
深度长尾学习 |
|
8 |
Trustworthy AI: From Principles to Practices |
可信人工智能 |
|
9 |
Masked Autoencoders Are Scalable Vision Learners |
自监督MAE |
|
10 |
人工智能的 10 个重大数理基础问题 |
数理基础 |