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Ruizhi Deng
Ruizhi Deng
Bestätigte E-Mail-Adresse bei sfu.ca
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Zitiert von
Zitiert von
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Characterizing adversarial examples based on spatial consistency information for semantic segmentation
C Xiao, R Deng, B Li, F Yu, M Liu, D Song
Proceedings of the European Conference on Computer Vision (ECCV), 217-234, 2018
1102018
Sparsely aggregated convolutional networks
L Zhu, R Deng, M Maire, Z Deng, G Mori, P Tan
Proceedings of the European Conference on Computer Vision (ECCV), 186-201, 2018
692018
Advit: Adversarial frames identifier based on temporal consistency in videos
C Xiao, R Deng, B Li, T Lee, B Edwards, J Yi, D Song, M Liu, I Molloy
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
552019
Modeling continuous stochastic processes with dynamic normalizing flows
R Deng, B Chang, MA Brubaker, G Mori, A Lehrmann
Advances in Neural Information Processing Systems 33, 7805-7815, 2020
502020
Continuous latent process flows
R Deng, MA Brubaker, G Mori, A Lehrmann
Advances in Neural Information Processing Systems 34, 5162-5173, 2021
152021
Point process flows
N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ...
arXiv preprint arXiv:1910.08281, 2019
152019
Polydiffuse: Polygonal shape reconstruction via guided set diffusion models
J Chen, R Deng, Y Furukawa
Advances in Neural Information Processing Systems 36, 2024
62024
Sparsely connected convolutional networks
L Zhu, R Deng, Z Deng, G Mori, P Tan
arXiv preprint arXiv:1801.05895, 2018
42018
Learning to forecast videos of human activity with multi-granularity models and adaptive rendering
M Zhai, J Chen, R Deng, L Chen, L Zhu, G Mori
arXiv preprint arXiv:1712.01955, 2017
32017
Systems and methods for modeling continuous stochastic processes with dynamic normalizing flows
D Ruizhi, B Chang, MA Brubaker, GP Mori, ASM Lehrmann
US Patent App. 17/170,416, 2021
22021
Adaptive appearance rendering
M Zhai, R Deng, J Chen, L Chen, Z Deng, G Mori
arXiv preprint arXiv:2104.11931, 2021
22021
Variational hyper rnn for sequence modeling
R Deng, Y Cao, B Chang, L Sigal, G Mori, MA Brubaker
arXiv preprint arXiv:2002.10501, 2020
22020
System and method for machine learning architecture with variational hyper-RNN
D Ruizhi, CAO Yanshuai, B Chang, M Brubaker
US Patent 11,615,305, 2023
12023
Conditional Diffusion Models as Self-supervised Learning Backbone for Irregular Time Series
H Shirzad, R Deng, H Zhao, F Tung
ICLR 2024 Workshop on Learning from Time Series For Health, 2024
2024
Pretext Training Algorithms for Event Sequence Data
Y Wang, H Zhao, R Deng, F Tung, G Mori
arXiv preprint arXiv:2402.10392, 2024
2024
System and method for continuous dynamics model from irregular time-series data
D Ruizhi, MA Brubaker, GP Mori, ASM Lehrmann
US Patent App. 17/749,678, 2022
2022
Continuous-time Particle Filtering for Latent Stochastic Differential Equations
R Deng, G Mori, AM Lehrmann
arXiv preprint arXiv:2209.00173, 2022
2022
Supplementary Document: PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models
J Chen, R Deng, Y Furukawa
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows Supplementary Materials
R Deng, B Chang, MA Brubaker, G Mori, A Lehrmann
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