Suchergebnisse - "beta-convolutional variational autoencoder"

History matching of a three dimensional channelized reservoir using a beta-convolutional variational autoencoder and ensemble smoother with multiple data assimilation

Autoren: Youngbin Ahn Jonggeun Choe Baehyun Min

Quelle: Engineering Applications of Artificial Intelligence. 159:111620

앙상블 기반 방법과 beta-convolutional variational autoencoder를 사용한 3차원 채널저류층 히스토리매칭 ; 3D Channel Reservoir History Matching Using Ensemble-Based Method and Beta-Convolutional Variational Autoencoder

Autoren: 안영빈 최종근 YoungBin Ahn et al.

Weitere Verfasser: 안영빈 최종근 YoungBin Ahn et al.

Schlagwörter: 히스토리매칭, 채널저류층, 3D 저류층, 앙상블 기반 방법, 기계 학습, beta-convolutional variational autoencoder, 622.33

Dateibeschreibung: xiii, 158

Relation: 000000178440; https://hdl.handle.net/10371/196356; https://dcollection.snu.ac.kr/common/orgView/000000178440; 000000000050▲000000000058▲000000178440▲

Verfügbarkeit: https://hdl.handle.net/10371/196356
https://dcollection.snu.ac.kr/common/orgView/000000178440

A deep-learning search for technosignatures of 820 nearby stars

Autoren: Ma, Peter Xiangyuan Ng, Cherry Rizk, Leandro et al.

Index Begriffe: Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2301.12670

Conducting Technosignature Search with Unsupervised Machine Learning Models

Autoren: Peter Ma

Relation: https://zenodo.org/communities/octopusassembly2021/; https://zenodo.org/records/5160163; oai:zenodo.org:5160163; https://doi.org/10.5281/zenodo.5160163

Verfügbarkeit: https://doi.org/10.5281/zenodo.5160163
https://zenodo.org/records/5160163

A deep-learning search for technosignatures from 820 nearby stars

Autoren: Peter Xiangyuan Ma Cherry Ng Leandro Rizk et al.

Quelle: Nature Astronomy.

Schlagwörter: FOS: Computer and information sciences, 0301 basic medicine, Computer Science - Machine Learning, SETI, human radiofrequency interference, FOS: Physical sciences, 7. Clean energy, 01 natural sciences, Machine Learning (cs.LG), 03 medical and health sciences, 13. Climate action, technosignature, 0103 physical sciences, Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM)

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2301.12670

Conducting Technosignature Search with Unsupervised Machine Learning Models

Autoren: Ma, Peter