ICLR
ML/AI Core
11,015 papers
· 2018–2025
ICLR (International Conference on Learning Representations) focuses on representation learning and deep learning, including neural network architectures, training methods, and generative models.
Papers per year
337
502
687
859
1,094
1,573
2,260
3,703
'20
'25
Top authors
Sergey Levine
90 papers
Yoshua Bengio
73 papers
Yang Liu
61 papers
Zhangyang Wang
58 papers
Junchi Yan
53 papers
Joshua B. Tenenbaum
45 papers
Tongliang Liu
44 papers
Bernhard Schölkopf
42 papers
Pieter Abbeel
42 papers
Bo Li
41 papers
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their counts at this venue are combined. How identity is handled.