Cover Image

Optimal Layer Selection for Latent Data Augmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Takase, Tomoumi, Karakida, Ryo
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hierarchical Associative Memory, Parallelized MLP-Mixer, and Symmetry Breaking
by: Karakida, Ryo, et al.
Published: (2024)

TAROT: Targeted Data Selection via Optimal Transport
by: Feng, Lan, et al.
Published: (2024)

Leveraging Latent Diffusion Models for Training-Free In-Distribution Data Augmentation for Surface Defect Detection
by: Girella, Federico, et al.
Published: (2024)

Leveraging Data to Say No: Memory Augmented Plug-and-Play Selective Prediction
by: Sarkar, Aditya, et al.
Published: (2026)

When Dynamic Data Selection Meets Data Augmentation
by: Yang, Suorong, et al.
Published: (2025)

Theoretical Guarantees of Data Augmented Last Layer Retraining Methods
by: Welfert, Monica, et al.
Published: (2024)

MALT Diffusion: Memory-Augmented Latent Transformers for Any-Length Video Generation
by: Yu, Sihyun, et al.
Published: (2025)

Latent Code Augmentation Based on Stable Diffusion for Data-free Substitute Attacks
by: Shao, Mingwen, et al.
Published: (2023)

An Optimal Transport-driven Approach for Cultivating Latent Space in Online Incremental Learning
by: Tran, Quyen, et al.
Published: (2022)

Gradient-Guided Exploration of Generative Model's Latent Space for Controlled Iris Image Augmentations
by: Mitcheff, Mahsa, et al.
Published: (2025)

Data Augmentation For Small Object using Fast AutoAugment
by: Yoon, DaeEun, et al.
Published: (2025)

Generative Spatiotemporal Data Augmentation
by: Zhou, Jinfan, et al.
Published: (2025)

Weakly Semi-supervised Tool Detection in Minimally Invasive Surgery Videos
by: Fujii, Ryo, et al.
Published: (2024)

Generative Latent Diffusion for Efficient Spatiotemporal Data Reduction
by: Li, Xiao, et al.
Published: (2025)

Model Debiasing by Learnable Data Augmentation
by: Morerio, Pietro, et al.
Published: (2024)

LIFT: Latent Implicit Functions for Task- and Data-Agnostic Encoding
by: Kazerouni, Amirhossein, et al.
Published: (2025)

DRO-Augment Framework: Robustness by Synergizing Wasserstein Distributionally Robust Optimization and Data Augmentation
by: Hu, Jiaming, et al.
Published: (2025)

SeA: Semantic Adversarial Augmentation for Last Layer Features from Unsupervised Representation Learning
by: Qian, Qi, et al.
Published: (2024)

Robustness of Visual Explanations to Common Data Augmentation
by: Tětková, Lenka, et al.
Published: (2023)

Data-Augmented Quantization-Aware Knowledge Distillation
by: Kur, Justin, et al.
Published: (2025)

Controlled Face Manipulation and Synthesis for Data Augmentation
by: Kirchner, Joris, et al.
Published: (2026)

Efficient Long-Tail Learning in Latent Space by sampling Synthetic Data
by: Sharma, Nakul
Published: (2025)

Exploring the Possibility of TypiClust for Low-Budget Federated Active Learning
by: Ono, Yuta, et al.
Published: (2025)

GeoMix: Towards Geometry-Aware Data Augmentation
by: Zhao, Wentao, et al.
Published: (2024)

Understanding the Detrimental Class-level Effects of Data Augmentation
by: Kirichenko, Polina, et al.
Published: (2023)

Diffusion-Based Data Augmentation for Medical Image Segmentation
by: Nazir, Maham, et al.
Published: (2025)

Group Relative Augmentation for Data Efficient Action Detection
by: Patel, Deep Anil, et al.
Published: (2025)

Towards Understanding Why Data Augmentation Improves Generalization
by: Li, Jingyang, et al.
Published: (2025)

MetaAug: Meta-Data Augmentation for Post-Training Quantization
by: Pham, Cuong, et al.
Published: (2024)

Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise
by: Zhang, Hongyuan, et al.
Published: (2024)

Latent Diffusion Inversion Requires Understanding the Latent Space
by: Rao, Mingxing, et al.
Published: (2025)

LatentGAN Autoencoder: Learning Disentangled Latent Distribution
by: Kalwar, Sanket, et al.
Published: (2022)

JLT: Clean-Latent Prediction in Latent Diffusion Transformers
by: Fu, Funing, et al.
Published: (2026)

What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context
by: Wang, Jing, et al.
Published: (2024)

On the Mechanisms of Adversarial Data Augmentation for Robust and Adaptive Transfer Learning
by: Satou, Hana, et al.
Published: (2025)

HandCraft: Dynamic Sign Generation for Synthetic Data Augmentation
by: Rios, Gaston Gustavo, et al.
Published: (2025)

Analyzing Effects of Mixed Sample Data Augmentation on Model Interpretability
by: Won, Soyoun, et al.
Published: (2023)

Adversarial Robustness for Deep Learning-based Wildfire Prediction Models
by: Ide, Ryo, et al.
Published: (2024)

Symbol-Aware Reasoning with Masked Discrete Diffusion for Handwritten Mathematical Expression Recognition
by: Kawakatsu, Takaya, et al.
Published: (2026)

Scaling-based Data Augmentation for Generative Models and its Theoretical Extension
by: Koike, Yoshitaka, et al.
Published: (2024)