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Computer Science 논문 리뷰
Computer Science 분야 주요 연구 논문을 연구 동기·방법·결과로 구조화한 AI 논문 리뷰 목록입니다.
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필터
9999+개의 결과
LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond
Wenbo Li, Kun Zhou 외 4명
arXiv (Cornell University)
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2021
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107 회 인용
Learning to Decompose and Disentangle Representations for Video Prediction
Jun-Ting Hsieh, Bingbin Liu 외 3명
arXiv (Cornell University)
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2018
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107 회 인용
Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines
Ben Mildenhall, Pratul P. Srinivasan 외 5명
arXiv (Cornell University)
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2019
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107 회 인용
Localizing Objects with Self-Supervised Transformers and no Labels
Oriane Siméoni, Gilles Puy 외 7명
arXiv (Cornell University)
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2021
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107 회 인용
NeuroRule: A Connectionist Approach to Data Mining
Hongjun Lü, Rudy Setiono 외 1명
arXiv (Cornell University)
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2017
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107 회 인용
Not All Samples Are Created Equal: Deep Learning with Importance Sampling
Angelos Katharopoulos, François Fleuret
arXiv (Cornell University)
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2018
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107 회 인용
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes
Xiaoyu Li, Francesco Orabona
arXiv (Cornell University)
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2018
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107 회 인용
On the Predictive Power of Neural Language Models for Human Real-Time Comprehension Behavior
Ethan Wilcox, Jon Gauthier 외 3명
arXiv (Cornell University)
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2020
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107 회 인용
One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers
Ari S. Morcos, Haonan Yu 외 2명
arXiv (Cornell University)
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2019
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107 회 인용
Overfitting Mechanism and Avoidance in Deep Neural Networks
Shaeke Salman, Xiuwen Liu
arXiv (Cornell University)
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2019
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107 회 인용
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