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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
Emergent Tool Use From Multi-Agent Autocurricula
Bowen Baker, Ingmar Kanitscheider 외 5명
arXiv (Cornell University)
|
2019
|
335 회 인용
Fractional Max-Pooling
Benjamin Graham
arXiv (Cornell University)
|
2014
|
335 회 인용
MADE: Masked Autoencoder for Distribution Estimation
Mathieu Germain, Karol Gregor 외 2명
arXiv (Cornell University)
|
2015
|
335 회 인용
Matterport3D: Learning from RGB-D Data in Indoor Environments
Anne Lynn S. Chang, Angela Dai 외 7명
arXiv (Cornell University)
|
2017
|
334 회 인용
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Jakob Foerster, Nantas Nardelli 외 5명
arXiv (Cornell University)
|
2017
|
333 회 인용
Peer-to-Peer Communication Across Network Address Translators
Bryan Ford, P. Srisuresh 외 1명
ArXiv.org
|
2006
|
332 회 인용
What Does Explainable AI Really Mean? A New Conceptualization of Perspectives
Derek Doran, Sarah Schulz 외 1명
arXiv (Cornell University)
|
2017
|
332 회 인용
Billion-scale semi-supervised learning for image classification
İsmet Zeki Yalnız, Hervé Jeǵou 외 3명
arXiv (Cornell University)
|
2019
|
331 회 인용
D4RL: Datasets for Deep Data-Driven Reinforcement Learning
Justin Fu, Aviral Kumar 외 3명
arXiv (Cornell University)
|
2020
|
331 회 인용
Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation
Nima Tajbakhsh, Laura Jeyaseelan 외 4명
arXiv (Cornell University)
|
2019
|
331 회 인용
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