Research

Papers for “imagenet”

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

Title	Authors	Year	Source
Improving Diffusion Model Efficiency Through Patching	Troy Luhman, Eric Luhman	2022	arxiv 2207.04316
Mathematical Challenges in Deep Learning	Vahid Partovi Nia, Guojun Zhang, Ivan Kobyzev	2023	arxiv 2303.15464
Some Improvements on Deep Convolutional Neural Network Based Image Classification	Andrew G. Howard	2013	arxiv 1312.5402
Improving Visual Quality of Unrestricted Adversarial Examples with Wavelet-VAE	Wenzhao Xiang, Chang Liu, Shibao Zheng	2021	arxiv 2108.11032
Nonlinear Acceleration of CNNs	Damien Scieur, Edouard Oyallon, Alexandre d'Aspremont	2018	arxiv 1806.00370
Transfer Learning with Sparse Associative Memories	Quentin Jodelet, Vincent Gripon, Masafumi Hagiwara	2019	arxiv 1904.02420
The SaTML '24 CNN Interpretability Competition: New Innovations for Concept-Level Interpretability	Stephen Casper, Jieun Yun, Joonhyuk Baek	2024	arxiv 2404.02949
Is Attentional Channel Processing Design Required? Comprehensive Analysis Of Robustness Between Vision Transformers And Fully Attentional Networks	Abhishri Ajit Medewar, Swanand Ashokrao Kavitkar	2023	arxiv 2306.05495
Linear Diffusion Networks	Jacob Fein-Ashley	2025	arxiv 2502.12381
Connecting Sphere Manifolds Hierarchically for Regularization	Damien Scieur, Youngsung Kim	2021	arxiv 2106.13549
Combining Deep Learning with Good Old-Fashioned Machine Learning	Moshe Sipper	2022	arxiv 2207.03757
Training Deeper Convolutional Networks with Deep Supervision	Liwei Wang, Chen-Yu Lee, Zhuowen Tu	2015	arxiv 1505.02496
Universum Prescription: Regularization using Unlabeled Data	Xiang Zhang, Yann LeCun	2015	arxiv 1511.03719
Approximation Algorithms for Cascading Prediction Models	Matthew Streeter	2018	arxiv 1802.07697
Using accumulation to optimize deep residual neural nets	Yatin Saraiya	2018	arxiv 1803.05778
A Generalizable Approach to Learning Optimizers	Diogo Almeida, Clemens Winter, Jie Tang	2021	arxiv 2106.00958
Robust Classification by Coupling Data Mollification with Label Smoothing	Markus Heinonen, Ba-Hien Tran, Michael Kampffmeyer	2024	arxiv 2406.01494
End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer	Wenda Chu, Bingliang Zhang, Jiaqi Han	2026	arxiv 2605.00503
Unified Latents (UL): How to train your latents	Jonathan Heek, Emiel Hoogeboom, Thomas Mensink	2026	arxiv 2602.17270
Improving Contrastive Learning by Visualizing Feature Transformation	Rui Zhu, Bingchen Zhao, Jingen Liu	2021	arxiv 2108.02982

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