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Distilling the Knowledge in a Neural Network
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2015
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Geoffrey E. Hinton
Oriol Vinyals
Jay B. Dean
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1
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ImageNet Large Scale Visual Recognition Challenge
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2015
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Olga Russakovsky
Jia Deng
Hao Su
Jonathan Krause
Sanjeev Satheesh
Sean Ma
Zhiheng Huang
Andrej Karpathy
Aditya Khosla
Michael S. Bernstein
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1
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Deep Unsupervised Learning using Nonequilibrium Thermodynamics
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2015
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Jascha Sohl‐Dickstein
Eric A. Weiss
Niru Maheswaranathan
Surya Ganguli
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1
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Deep Residual Learning for Image Recognition
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2016
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Kaiming He
Xiangyu Zhang
Shaoqing Ren
Jian Sun
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1
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Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
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2013
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Yoshua Bengio
Nicholas Léonard
Aaron Courville
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1
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Perceptual Losses for Real-Time Style Transfer and Super-Resolution
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2016
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Justin Johnson
Alexandre Alahi
Li Fei-Fei
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1
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DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
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2016
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Shuchang Zhou
Yuxin Wu
Zekun Ni
Xinyu Zhou
He Wen
Yuheng Zou
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1
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Towards Accurate Multi-person Pose Estimation in the Wild
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2017
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George Papandreou
Tyler Zhu
Nori Kanazawa
Alexander Toshev
Jonathan Tompson
Chris Bregler
Kevin Murphy
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1
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Deep Learning with Low Precision by Half-Wave Gaussian Quantization
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2017
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Zhaowei Cai
Xiaodong He
Jian Sun
Nuno Vasconcelos
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1
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To prune, or not to prune: exploring the efficacy of pruning for model compression
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2017
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Michael Zhu
Suyog Gupta
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1
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PACT: Parameterized Clipping Activation for Quantized Neural Networks
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2018
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Jungwook Choi
Zhuo Wang
Swagath Venkataramani
Pierce Chuang
Vijayalakshmi Srinivasan
Kailash Gopalakrishnan
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1
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Quantizing deep convolutional networks for efficient inference: A whitepaper
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2018
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Raghuraman Krishnamoorthi
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1
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Toward Characteristic-Preserving Image-Based Virtual Try-On Network
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2018
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Bochao Wang
Huabin Zheng
Xiaodan Liang
Yimin Chen
Liang Lin
Meng Yang
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1
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LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks
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2018
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Dongqing Zhang
Jiaolong Yang
Dongqiangzi Ye
Gang Hua
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1
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Rethinking the Value of Network Pruning
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2018
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Zhuang Liu
Mingjie Sun
Tinghui Zhou
Gao Huang
Trevor Darrell
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1
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Improving Neural Network Quantization without Retraining using Outlier Channel Splitting
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2019
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Ritchie Zhao
Yuwei Hu
Jordan Dotzel
Christopher De
Zhiru Zhang
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1
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Learned Step Size Quantization
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2019
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Steven K. Esser
Jeffrey L. McKinstry
Deepika Bablani
Rathinakumar Appuswamy
Dharmendra S. Modha
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1
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Large Scale GAN Training for High Fidelity Natural Image Synthesis
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2018
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Andrew Brock
Jeff Donahue
Karen Simonyan
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1
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Generative Modeling by Estimating Gradients of the Data Distribution
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2019
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Yang Song
Stefano Ermon
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1
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Value-Aware Quantization for Training and Inference of Neural Networks
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2018
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Eunhyeok Park
Sungjoo Yoo
Péter Vajda
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1
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Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference
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2018
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Benoit Jacob
Skirmantas Kligys
Bo Chen
Menglong Zhu
Matthew F. Tang
Andrew Howard
Hartwig Adam
Dmitry Kalenichenko
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1
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MobileNetV2: Inverted Residuals and Linear Bottlenecks
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2018
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Mark Sandler
Andrew Howard
Menglong Zhu
Andrey Zhmoginov
Liang-Chieh Chen
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1
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Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss
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2019
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Sangil Jung
Changyong Son
Seohyung Lee
Jinwoo Son
Jae‐Joon Han
Youngjun Kwak
Sung Ju Hwang
Changkyu Choi
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1
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Theory of Deep Learning III: explaining the non-overfitting puzzle
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2018
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Tomaso Poggio
Kenji Kawaguchi
Qianli Liao
Brando Miranda
Lorenzo Rosasco
Xavier Boix
Jack D. Hidary
H. N. Mhaskar
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1
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MnasNet: Platform-Aware Neural Architecture Search for Mobile
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2019
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Mingxing Tan
Bo Chen
Ruoming Pang
Vijay Vasudevan
Mark Sandler
Andrew Howard
Quoc V. Le
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1
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VITON: An Image-Based Virtual Try-on Network
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2018
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Xintong Han
Zuxuan Wu
Zhe Wu
Ruichi Yu
Larry S. Davis
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1
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Graphonomy: Universal Human Parsing via Graph Transfer Learning
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2019
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Ke Gong
Yiming Gao
Xiaodan Liang
Xiaohui Shen
Meng Wang
Liang Lin
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1
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Model compression via distillation and quantization
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2018
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Antonio Polino
Razvan Pascanu
Dan Alistarh
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1
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HAQ: Hardware-Aware Automated Quantization With Mixed Precision
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2019
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Kuan Wang
Zhijian Liu
Yujun Lin
Ji Lin
Song Han
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1
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Low-bit Quantization of Neural Networks for Efficient Inference
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2019
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Yoni Choukroun
Eli Kravchik
Fan Yang
Pavel Kisilev
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1
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Designing Network Design Spaces
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2020
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Ilija Radosavovic
Raj Prateek Kosaraju
Ross Girshick
Kaiming He
Piotr Dollár
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1
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Training Generative Adversarial Networks with Limited Data
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2020
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Tero Karras
Miika Aittala
Janne Hellsten
Samuli Laine
Jaakko Lehtinen
Timo Aila
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1
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ZeroQ: A Novel Zero Shot Quantization Framework
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2020
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Yaohui Cai
Zhewei Yao
Zhen Dong
Amir Gholami
Michael W. Mahoney
Kurt Keutzer
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1
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The Knowledge Within: Methods for Data-Free Model Compression
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2020
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Matan Haroush
Itay Hubara
Elad Hoffer
Daniel Soudry
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1
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Controllable Person Image Synthesis With Attribute-Decomposed GAN
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2020
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Yifang Men
Yiming Mao
Yuning Jiang
Wei‐Ying Ma
Zhouhui Lian
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1
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Analyzing and Improving the Image Quality of StyleGAN
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2020
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Tero Karras
Samuli Laine
Miika Aittala
Janne Hellsten
Jaakko Lehtinen
Timo Aila
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1
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Denoising Diffusion Probabilistic Models
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2020
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Jonathan Ho
Ajay N. Jain
Pieter Abbeel
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1
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EasyQuant: Post-training Quantization via Scale Optimization
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2020
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Di Wu
Qi Tang
Zhao Yong-le
Ming Zhang
Fu Ying
Debing Zhang
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1
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Generative adversarial networks
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2020
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Ian Goodfellow
Jean Pouget-Abadie
Mehdi Mirza
Bing Xu
David Warde-Farley
Sherjil Ozair
Aaron Courville
Yoshua Bengio
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1
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Generative Low-Bitwidth Data Free Quantization
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2020
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Shoukai Xu
Haokun Li
Bohan Zhuang
Jing Liu
Jiezhang Cao
Chuangrun Liang
Mingkui Tan
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1
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Post-training Piecewise Linear Quantization for Deep Neural Networks
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2020
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Jun Fang
Ali Shafiee
Hamzah Abdel-Aziz
David Thorsley
Georgios Georgiadis
Joseph Hassoun
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1
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Do Not Mask What You Do Not Need to Mask: A Parser-Free Virtual Try-On
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2020
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Thibaut Issenhuth
Jérémie Mary
Clément Calauzènes
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1
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Denoising Diffusion Implicit Models
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2020
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Jiaming Song
Chenlin Meng
Stefano Ermon
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1
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A Survey of Quantization Methods for Efficient Neural Network Inference
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2022
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Amir Gholami
Sehoon Kim
Zhen Dong
Zhewei Yao
Michael W. Mahoney
Kurt Keutzer
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1
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Image Super-Resolution Via Iterative Refinement
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2022
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Chitwan Saharia
Jonathan Ho
William Chan
Tim Salimans
David J. Fleet
Mohammad Norouzi
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1
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Learning Transferable Visual Models From Natural Language Supervision
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2021
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Alec Radford
Jong Wook Kim
Chris Hallacy
Aditya Ramesh
Gabriel Goh
Sandhini Agarwal
Girish Sastry
Amanda Askell
Pamela Mishkin
Jack Clark
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1
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BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
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2021
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Yuhang Li
Ruihao Gong
Xu Tan
Yang Yang
Peng Hu
Qi Zhang
Fengwei Yu
Wei Wang
Shi Gu
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1
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VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization
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2021
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Seung-Hwan Choi
Sunghyun Park
Minsoo Lee
Jaegul Choo
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1
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Diversifying Sample Generation for Accurate Data-Free Quantization
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2021
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Xiangguo Zhang
Haotong Qin
Yifu Ding
Ruihao Gong
Qinghua Yan
Renshuai Tao
Yuhang Li
Fengwei Yu
Xianglong Liu
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1
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Cascaded Diffusion Models for High Fidelity Image Generation
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2021
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Jonathan Ho
Chitwan Saharia
William Chan
David J. Fleet
Mohammad Norouzi
Tim Salimans
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1
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