Learning Interpretable Deep State Space Model for Probabilistic Time
Series Forecasting

Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting

31 January 2021

Papers citing "Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting"

10 / 10 papers shown

Title
STAN: Smooth Transition Autoregressive Networks Hugo Inzirillo Remi Genet 63 0 0 30 Jan 2025
A Gated Residual Kolmogorov-Arnold Networks for Mixtures of Experts Hugo Inzirillo Remi Genet MoE 35 4 0 23 Sep 2024
Large Pre-trained time series models for cross-domain Time series analysis tasks Harshavardhan Kamarthi B. A. Prakash VLM AI4TS 15 10 0 19 Nov 2023
When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting Harshavardhan Kamarthi Lingkai Kong Alexander Rodríguez Chao Zhang B. Prakash AI4TS 33 5 0 17 Oct 2023
Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation Jinyi Hu Xiaoyuan Yi Wenhao Li Maosong Sun Xingxu Xie DRL 21 0 0 22 Oct 2022
AA-Forecast: Anomaly-Aware Forecast for Extreme Events Ashkan Farhangi Jiang Bian Arthur Huang Haoyi Xiong Jun Wang Zhi-guo Guo AI4TS 29 4 0 21 Aug 2022
Why Did This Model Forecast This Future? Closed-Form Temporal Saliency Towards Causal Explanations of Probabilistic Forecasts Chirag Raman Hayley Hung Marco Loog 21 3 0 01 Jun 2022
SSDNet: State Space Decomposition Neural Network for Time Series Forecasting Yang Lin I. Koprinska Mashud Rana BDL AI4TS 26 31 0 19 Dec 2021
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting Soumyasundar Pal Liheng Ma Yingxue Zhang Mark J. Coates BDL AI4TS 31 22 0 10 Jun 2021
Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems Haitao Liu Changjun Liu Xiaomo Jiang Xudong Chen Shuhua Yang Xiaofang Wang BDL AI4TS 27 2 0 03 Jun 2021