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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
Model-Ensemble Trust-Region Policy Optimization
Thanard Kurutach, Ignasi Clavera 외 3명
arXiv (Cornell University)
|
2018
|
218 회 인용
Object-Centric Learning with Slot Attention
Francesco Locatello, Dirk Weissenborn 외 6명
arXiv (Cornell University)
|
2020
|
218 회 인용
Spectral Norm Regularization for Improving the Generalizability of Deep Learning
Yuichi Yoshida, Takeru Miyato
arXiv (Cornell University)
|
2017
|
218 회 인용
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
Takeru Miyato, Shin‐ichi Maeda 외 2명
arXiv (Cornell University)
|
2017
|
218 회 인용
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
David Bau, Jun-Yan Zhu 외 5명
arXiv (Cornell University)
|
2018
|
217 회 인용
Instantaneous and lagged measurements of linear and nonlinear dependence between groups of multivariate time series: frequency decomposition
Roberto D. Pascual‐Marqui
ArXiv.org
|
2007
|
217 회 인용
Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation
Hao Wu, Patrick Judd 외 3명
arXiv (Cornell University)
|
2020
|
217 회 인용
Meta-Learning with Implicit Gradients
Aravind Rajeswaran, Chelsea Finn 외 2명
arXiv (Cornell University)
|
2019
|
217 회 인용
MOPO: Model-based Offline Policy Optimization
Tianhe Yu, Garrett Thomas 외 6명
arXiv (Cornell University)
|
2020
|
217 회 인용
MPDIoU: A Loss for Efficient and Accurate Bounding Box Regression
Siliang Ma, Yong Xu
arXiv (Cornell University)
|
2023
|
217 회 인용
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