Human Interpretable Radar Through Deep Generative Models

被引：0
|
作者：
Dvorecki, Nir [1 ]
Amizur, Yuval [1 ]
Banin, Leor [1 ]
机构：
[1] Mobileye, Jerusalem, Israel
来源：
2022 52ND EUROPEAN MICROWAVE CONFERENCE (EUMC) | 2022年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
引用
收藏
页数：1
相关论文
共 50 条
  • [1] Human Interpretable Radar Through Deep Generative Models
    Dvorecki, Nir
    Amizur, Yuval
    Banin, Leor
    [J]. 2022 19TH EUROPEAN RADAR CONFERENCE (EURAD), 2022, : 389 - 392
  • [2] Human Interpretable Radar Through Deep Generative Models
    Dvorecki, Nir
    Amizur, Yuval
    Banin, Leor
    [J]. 2022 52ND EUROPEAN MICROWAVE CONFERENCE (EUMC), 2022,
  • [3] Human Interpretable Radar Through Deep Generative Models
    Dvorecki, Nir
    Amizur, Yuval
    Banin, Leor
    [J]. 2022 19th European Radar Conference, EuRAD 2022, 2022, : 389 - 392
  • [4] Interpretable Deep Generative Recommendation Models
    Liu, Huafeng
    Jing, Liping
    Wen, Jingxuan
    Xu, Pengyu
    Wang, Jiaqi
    Yu, Jian
    Ng, Michael K.
    [J]. JOURNAL OF MACHINE LEARNING RESEARCH, 2021, 22
  • [5] Interpretable deep generative recommendation models
    Liu, Huafeng
    Jing, Liping
    Wen, Jingxuan
    Xu, Pengyu
    Wang, Jiaqi
    Yu, Jian
    Ng, Michael K.
    [J]. Journal of Machine Learning Research, 2021, 22
  • [6] Learning Interpretable Anatomical Features Through Deep Generative Models: Application to Cardiac Remodeling
    Biffi, Carlo
    Oktay, Ozan
    Tarroni, Giacomo
    Bai, Wenjia
    De Marvao, Antonio
    Doumou, Georgia
    Rajchl, Martin
    Bedair, Reem
    Prasad, Sanjay
    Cook, Stuart
    O'Regan, Declan
    Rueckert, Daniel
    [J]. MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT II, 2018, 11071 : 464 - 471
  • [7] Discovering Interpretable Representations for Both Deep Generative and Discriminative Models
    Adel, Tameem
    Ghahramani, Zoubin
    Weller, Adrian
    [J]. INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 80, 2018, 80
  • [8] siVAE: interpretable deep generative models for single-cell transcriptomes
    Choi, Yongin
    Li, Ruoxin
    Quon, Gerald
    [J]. GENOME BIOLOGY, 2023, 24 (01)
  • [9] siVAE: interpretable deep generative models for single-cell transcriptomes
    Yongin Choi
    Ruoxin Li
    Gerald Quon
    [J]. Genome Biology, 24
  • [10] Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
    Ding, Jiarui
    Condon, Anne
    Shah, Sohrab P.
    [J]. NATURE COMMUNICATIONS, 2018, 9
12345