ICML "data augmentation" Papers
11 papers found
ATraDiff: Accelerating Online Reinforcement Learning with Imaginary Trajectories
Qianlan Yang, Yu-Xiong Wang
ICML 2024poster
Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation
Yididiya Nadew, Xuhui Fan, Christopher J Quinn
ICML 2024poster
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation
Zelin Zang, Hao Luo, Kai Wang et al.
ICML 2024poster
DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching
Guanghe Li, Yixiang Shan, Zhengbang Zhu et al.
ICML 2024poster
Emergent Equivariance in Deep Ensembles
Jan Gerken, Pan Kessel
ICML 2024poster
EquiAV: Leveraging Equivariance for Audio-Visual Contrastive Learning
Jongsuk Kim, Hyeongkeun Lee, Kyeongha Rho et al.
ICML 2024poster
First-Order Manifold Data Augmentation for Regression Learning
Ilya Kaufman, Omri Azencot
ICML 2024poster
Improved Generalization of Weight Space Networks via Augmentations
Aviv Shamsian, Aviv Navon, David Zhang et al.
ICML 2024poster
Sample-Efficient Multiagent Reinforcement Learning with Reset Replay
Yaodong Yang, Guangyong Chen, Jianye Hao et al.
ICML 2024poster
Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup
Damien Teney, Jindong Wang, Ehsan Abbasnejad
ICML 2024poster
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective
Chi-Heng Lin, Chiraag Kaushik, Eva Dyer et al.
ICML 2024poster