RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting

RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting

10 June 2021

Soumyasundar Pal

Papers citing "RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting"

14 / 14 papers shown

Title
Learning Energy-Based Generative Models via Potential Flow: A Variational Principle Approach to Probability Density Homotopy Matching Junn Yong Loo Michelle Adeline Julia Kaiwen Lau Fang Yu Leong Hwa Hui Tew Arghya Pal Vishnu Monn Baskaran Chee-Ming Ting Raphaël C.-W. Phan BDL 61 0 0 22 Apr 2025
Variational Potential Flow: A Novel Probabilistic Framework for Energy-Based Generative Modelling Junn Yong Loo Michelle Adeline Arghya Pal Vishnu Monn Baskaran Chee-Ming Ting Raphaël C.-W. Phan DiffM 36 0 0 21 Jul 2024
OXYGENERATOR: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning Bin Lu Ze Zhao Luyu Han Xiaoying Gan Yuntao Zhou Lei Zhou Luoyi Fu Xinbing Wang Cheng Zhou Jing Zhang AI4Cl AI4CE 36 3 0 12 May 2024
LINOCS: Lookahead Inference of Networked Operators for Continuous Stability Noga Mudrik Eva Yezerets Yenho Chen Christopher Rozell Adam S. Charles AI4CE 22 4 0 28 Apr 2024
SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting Lequan Lin Dai Shi Andi Han Junbin Gao DiffM AI4TS 11 5 0 16 Jan 2024
Graph Deep Learning for Time Series Forecasting Andrea Cini Ivan Marisca Daniele Zambon C. Alippi AI4TS AI4CE 24 14 0 24 Oct 2023
Unsupervised Cross-Domain Soft Sensor Modelling via Deep Physics-Inspired Particle Flow Bayes Junn Yong Loo Ze Yang Ding Surya G. Nurzaman C. Ting Vishnu Monn Baskaran Chee Pin Tan OOD 13 0 0 08 Jun 2023
Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems Andreas Look M. Kandemir Barbara Rakitsch Jan Peters BDL 25 6 0 02 May 2023
Learning Mixture Structure on Multi-Source Time Series for Probabilistic Forecasting Tianli Guo AI4TS 25 0 0 22 Feb 2023
DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models Haomin Wen Youfang Lin Yutong Xia Huaiyu Wan Qingsong Wen Roger Zimmermann Yuxuan Liang DiffM 23 81 0 31 Jan 2023
Graph state-space models Daniele Zambon Andrea Cini L. Livi C. Alippi 23 6 0 04 Jan 2023
Sub-Graph Learning for Spatiotemporal Forecasting via Knowledge Distillation Mehrtash Mehrabi Yingxue Zhang 20 0 0 17 Nov 2022
Taming the Long Tail of Deep Probabilistic Forecasting Jedrzej Kozerawski Mayank Sharan Rose Yu AI4TS 13 7 0 27 Feb 2022
Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting Longyuan Li Junchi Yan Xiaokang Yang Yaohui Jin OOD BDL AI4TS 37 60 0 31 Jan 2021