Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder

11 August 2021

Papers citing "Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder"

9 / 9 papers shown

Title
Bridging Domain Gap of Point Cloud Representations via Self-Supervised Geometric Augmentation Li Yu Hongchao Zhong Longkun Zou Ke Chen Pan Gao 3DPC 36 0 0 11 Sep 2024
Exploring Cross-Domain Few-Shot Classification via Frequency-Aware Prompting Tiange Zhang Qing Cai Feng Gao Lin Qi Junyu Dong 36 1 0 24 Jun 2024
Improving Intrusion Detection with Domain-Invariant Representation Learning in Latent Space Padmaksha Roy Tyler Cody Himanshu Singhal Kevin Choi Ming Jin OOD 24 1 0 28 Dec 2023
Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning Ananth Balashankar Xiao Ma Aradhana Sinha Ahmad Beirami Yao Qin Jilin Chen Alex Beutel 24 2 0 25 Oct 2023
Domain Adaptive Few-Shot Open-Set Learning Debabrata Pal Deeptej More Sai Bhargav Dipesh Tamboli Vaneet Aggarwal Biplab Banerjee 24 2 0 22 Sep 2023
Generalized Cross-domain Multi-label Few-shot Learning for Chest X-rays Aroof Aimen Arsh Verma Makarand Tapaswi N. C. Krishnan 32 0 0 08 Sep 2023
Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey Huali Xu Shuaifeng Zhi Shuzhou Sun Vishal M. Patel Li Liu 32 13 0 15 Mar 2023
How to Fine-tune Models with Few Samples: Update, Data Augmentation, and Test-time Augmentation Yujin Kim Jaehoon Oh Sungnyun Kim Se-Young Yun 29 6 0 13 May 2022
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 323 11,681 0 09 Mar 2017