ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning

8 October 2021

Papers citing "ModeRNN: Harnessing Spatiotemporal Mode Collapse in Unsupervised Predictive Learning"

7 / 7 papers shown

Title
Deep learning for precipitation nowcasting: A survey from the perspective of time series forecasting Sojung An Tae-Jin Oh Eunha Sohn Donghyun Kim AI4TS 40 6 0 07 Jun 2024
SSLChange: A Self-supervised Change Detection Framework Based on Domain Adaptation Yitao Zhao Turgay Celik Nanqing Liu Feng Gao Heng-Chao Li 30 4 0 28 May 2024
ComS2T: A complementary spatiotemporal learning system for data-adaptive model evolution Zhen-Qiang Zhou Qihe Huang Binwu Wang Jianpeng Hou Kuo Yang Yuxuan Liang Yang Wang AI4TS 25 2 0 04 Mar 2024
SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence Wei Fang Yanqing Chen Jianhao Ding Zhaofei Yu T. Masquelier Ding Chen Liwei Huang Huihui Zhou Guoqi Li Yonghong Tian 18 193 0 25 Oct 2023
Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction Vincent Le Guen Nicolas Thome AI4CE PINN 78 287 0 03 Mar 2020
Learning to Decompose and Disentangle Representations for Video Prediction Jun-Ting Hsieh Bingbin Liu De-An Huang Li Fei-Fei Juan Carlos Niebles DRL 127 304 0 11 Jun 2018
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 201 7,884 0 13 Jun 2015