SOTA2 Research · papers

Papers for “imagenet”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

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20 indexed

Title	Authors	Year	Source
Resource and data efficient self supervised learning	Ozan Ciga, Tony Xu, Anne L. Martel	2021	arxiv 2109.01721
Class-Incremental Learning using Diffusion Model for Distillation and Replay	Quentin Jodelet, Xin Liu, Yin Jun Phua	2023	arxiv 2306.17560
SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners	Feng Liang, Yangguang Li, Diana Marculescu	2022	arxiv 2205.14540
Hindering Adversarial Attacks with Multiple Encrypted Patch Embeddings	AprilPyone MaungMaung, Isao Echizen, Hitoshi Kiya	2023	arxiv 2309.01620
Boosting Out-of-distribution Detection with Typical Features	Yao Zhu, YueFeng Chen, Chuanlong Xie	2022	arxiv 2210.04200
Scaling Vision Transformers	Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby	2021	arxiv 2106.04560
Confidence Calibration with Bounded Error Using Transformations	Sooyong Jang, Radoslav Ivanov, Insup Lee	2021	arxiv 2102.12680
Unsupervised Learning on Neural Network Outputs: with Application in Zero-shot Learning	Yao Lu	2015	arxiv 1506.00990
Single Path One-Shot Neural Architecture Search with Uniform Sampling	Zichao Guo, Xiangyu Zhang, Haoyuan Mu	2019	arxiv 1904.00420
Matching Networks for One Shot Learning	Oriol Vinyals, Charles Blundell, Timothy Lillicrap	2016	arxiv 1606.04080
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients