Research

Papers for “imagenet”

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

Title	Authors	Year	Source
LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks	Dongqing Zhang, Jiaolong Yang, Dongqiangzi Ye	2018	arxiv 1807.10029
BAM: Bottleneck Attention Module	Jongchan Park, Sanghyun Woo, Joon-Young Lee	2018	arxiv 1807.06514
t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern Data	David M. Chan, Roshan Rao, Forrest Huang	2018	arxiv 1807.11824
Shift-based Primitives for Efficient Convolutional Neural Networks	Huasong Zhong, Xianggen Liu, Yihui He	2018	arxiv 1809.08458
D\'ej\`a Vu: an empirical evaluation of the memorization properties of ConvNets	Alexandre Sablayrolles, Matthijs Douze, Cordelia Schmid	2018	arxiv 1809.06396
WildSAT: Learning Satellite Image Representations from Wildlife Observations	Rangel Daroya, Elijah Cole, Oisin Mac Aodha	2024	arxiv 2412.14428
Language Modeling Is Compression	Grégoire Delétang, Anian Ruoss, Paul-Ambroise Duquenne	2023	arxiv 2309.10668
Improving Generalization and Convergence by Enhancing Implicit Regularization	Mingze Wang, Jinbo Wang, Haotian He	2024	arxiv 2405.20763
Applying Vision Transformers on Spectral Analysis of Astronomical Objects	Luis Felipe Strano Moraes, Ignacio Becker, Pavlos Protopapas	2025	arxiv 2506.00294
On the Importance of Calibration in Semi-supervised Learning	Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj	2022	arxiv 2210.04783
CoMatch: Semi-supervised Learning with Contrastive Graph Regularization	Junnan Li, Caiming Xiong, Steven Hoi	2020	arxiv 2011.11183
Separation and Concentration in Deep Networks	John Zarka, Florentin Guth, Stéphane Mallat	2020	arxiv 2012.10424
HSCoNAS: Hardware-Software Co-Design of Efficient DNNs via Neural Architecture Search	Xiangzhong Luo, Di Liu, Shuo Huai	2021	arxiv 2103.08325
Preprint: Norm Loss: An efficient yet effective regularization method for deep neural networks	Theodoros Georgiou, Sebastian Schmitt, Thomas Bäck	2021	arxiv 2103.06583
ACE: Adaptive Confusion Energy for Natural World Data Distribution	Yen-Chi Hsu, Cheng-Yao Hong, Wan-Cyuan Fan	2019	arxiv 1910.12423
UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning	Zhigang Dai, Bolun Cai, Yugeng Lin	2021	arxiv 2103.10773
Intra-Class Uncertainty Loss Function for Classification	He Zhu, Shan Yu	2021	arxiv 2104.05298
Meta-learning for skin cancer detection using Deep Learning Techniques	Sara I. Garcia	2021	arxiv 2104.10775
A Joint Energy and Latency Framework for Transfer Learning over 5G Industrial Edge Networks	Bo Yang, Omobayode Fagbohungbe, Xuelin Cao	2021	arxiv 2104.09382
Width Transfer: On the (In)variance of Width Optimization	Ting-Wu Chin, Diana Marculescu, Ari S. Morcos	2021	arxiv 2104.13255

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