Research

Papers for “imagenet”

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

Title	Authors	Year	Source
Stable Consistency Tuning: Understanding and Improving Consistency Models	Fu-Yun Wang, Zhengyang Geng, Hongsheng Li	2024	arxiv 2410.18958
EM Distillation for One-step Diffusion Models	Sirui Xie, Zhisheng Xiao, Diederik P Kingma	2024	arxiv 2405.16852
Imperceptible Sample-Specific Backdoor to DNN with Denoising Autoencoder	Xiangqi Wang, Mingfu Xue, Kewei Chen	2023	arxiv 2302.04457
CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning	Charles Guille-Escuret, Pau Rodriguez, David Vazquez	2022	arxiv 2210.01742
Sparse Weight Activation Training	Md Aamir Raihan, Tor M. Aamodt	2020	arxiv 2001.01969
Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup	Guodong Xu, Ziwei Liu, Chen Change Loy	2020	arxiv 2012.09413
LambdaNetworks: Modeling Long-Range Interactions Without Attention	Irwan Bello	2021	arxiv 2102.08602
High-Performance Large-Scale Image Recognition Without Normalization	Andrew Brock, Soham De, Samuel L. Smith	2021	arxiv 2102.06171
Semantically-Conditioned Negative Samples for Efficient Contrastive Learning	James O' Neill, Danushka Bollegala	2021	arxiv 2102.06603
Model-Agnostic Graph Regularization for Few-Shot Learning	Ethan Shen, Maria Brbic, Nicholas Monath	2021	arxiv 2102.07077
HAO: Hardware-aware neural Architecture Optimization for Efficient Inference	Zhen Dong, Yizhao Gao, Qijing Huang	2021	arxiv 2104.12766
Transformed CNNs: recasting pre-trained convolutional layers with self-attention	Stéphane d'Ascoli, Levent Sagun, Giulio Biroli	2021	arxiv 2106.05795
Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder	Jonas Dippel, Matthias Lenga, Thomas Goerttler	2022	arxiv 2207.14508
Depth Contrast: Self-Supervised Pretraining on 3DPM Images for Mining Material Classification	Prakash Chandra Chhipa, Richa Upadhyay, Rajkumar Saini	2022	arxiv 2210.10633
ViT2EEG: Leveraging Hybrid Pretrained Vision Transformers for EEG Data	Ruiqi Yang, Eric Modesitt	2023	arxiv 2308.00454
Towards Inadequately Pre-trained Models in Transfer Learning	Andong Deng, Xingjian Li, Di Hu	2022	arxiv 2203.04668
Accelerating Large Batch Training via Gradient Signal to Noise Ratio (GSNR)	Guo-qing Jiang, Jinlong Liu, Zixiang Ding	2023	arxiv 2309.13681
Evaluating Self-Supervised Learning via Risk Decomposition	Yann Dubois, Tatsunori Hashimoto, Percy Liang	2023	arxiv 2302.03068
Deep Epitomic Convolutional Neural Networks	George Papandreou	2014	arxiv 1406.2732
WEPSAM: Weakly Pre-Learnt Saliency Model	Avisek Lahiri, Sourya Roy, Anirban Santara	2016	arxiv 1605.01101

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