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
Attentive Graph Neural Networks for Few-Shot Learning	Hao Cheng, Joey Tianyi Zhou, Wee Peng Tay	2020	arxiv 2007.06878
An Unsupervised Information-Theoretic Perceptual Quality Metric	Sangnie Bhardwaj, Ian Fischer, Johannes Ballé	2020	arxiv 2006.06752
Exploring Weight Symmetry in Deep Neural Networks	Xu Shell Hu, Sergey Zagoruyko, Nikos Komodakis	2018	arxiv 1812.11027
Object Detection in Video with Spatial-temporal Context Aggregation	Hao Luo, Lichao Huang, Han Shen	2019	arxiv 1907.04988
Transfusion: Understanding Transfer Learning for Medical Imaging	Maithra Raghu, Chiyuan Zhang, Jon Kleinberg	2019	arxiv 1902.07208
Universal Adversarial Training	Ali Shafahi, Mahyar Najibi, Zheng Xu	2018	arxiv 1811.11304
Biologically-Motivated Deep Learning Method using Hierarchical Competitive Learning	Takashi Shinozaki	2020	arxiv 2001.01121
A Simple Baseline for Low-Budget Active Learning	Kossar Pourahmadi, Parsa Nooralinejad, Hamed Pirsiavash	2021	arxiv 2110.12033
When Does Contrastive Visual Representation Learning Work?	Elijah Cole, Xuan Yang, Kimberly Wilber	2021	arxiv 2105.05837
StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets	Axel Sauer, Katja Schwarz, Andreas Geiger	2022	arxiv 2202.00273
Fast Predictive Uncertainty for Classification with Bayesian Deep Networks