# If You Like It, GAN It. Probabilistic Multivariate Times Series Forecast With GAN

arXiv: https://arxiv.org/abs/2005.01181 · HTML: https://mlsanity.com/paper/2005.01181/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 May 2020.

## Built on by (most cited first, 14 of 14)

- [Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion](https://mlsanity.com/paper/2211.02590/) (2022)
- [Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization](https://mlsanity.com/paper/2112.08217/) (2021)
- [A review of predictive uncertainty estimation with machine learning](https://mlsanity.com/paper/2209.08307/) (2022)
- [Spatio-temporal graph neural networks for multi-site PV power forecasting](https://mlsanity.com/paper/2107.13875/) (2021)
- [pTSE: A Multi-model Ensemble Method for Probabilistic Time Series Forecasting](https://mlsanity.com/paper/2305.11304/) (2023)
- [Diffusion Models for Time Series Forecasting: A Survey](https://mlsanity.com/paper/2507.14507/) (2025)
- [Deep Time Series Forecasting with Shape and Temporal Criteria](https://mlsanity.com/paper/2104.04610/) (2021)
- [Random Noise vs State-of-the-Art Probabilistic Forecasting Methods : A Case Study on CRPS-Sum Discrimination Ability](https://mlsanity.com/paper/2201.08671/) (2022)
- [VQ-AR: Vector Quantized Autoregressive Probabilistic Time Series Forecasting](https://mlsanity.com/paper/2205.15894/) (2022)
- [A Bayesian Generative Adversarial Network (GAN) to Generate Synthetic Time-Series Data, Application in Combined Sewer Flow Prediction](https://mlsanity.com/paper/2301.13733/) (2023)
- [Uncertainty Aware Neural Network from Similarity and Sensitivity](https://mlsanity.com/paper/2304.14925/) (2023)
- [VAEneu: A New Avenue for VAE Application on Probabilistic Forecasting](https://mlsanity.com/paper/2405.04252/) (2024)
- [ForecastGAN: A Decomposition-Based Adversarial Framework for Multi-Horizon Time Series Forecasting](https://mlsanity.com/paper/2511.04445/) (2025)
- [EMFusion: Uncertainty-Aware Conditional Diffusion Model for Multivariate Narrow-band Exposure Forecasting](https://mlsanity.com/paper/2512.15067/) (2025)

## Abstract (arXiv)

The contribution of this paper is two-fold. First, we present ProbCast - a novel probabilistic model for multivariate time-series forecasting. We employ a conditional GAN framework to train our model with adversarial training. Second, we propose a framework that lets us transform a deterministic model into a probabilistic one with improved performance. The motivation of the framework is to either transform existing highly accurate point forecast models to their probabilistic counterparts or to train GANs stably by selecting the architecture of GAN's component carefully and efficiently. We conduct experiments over two publicly available datasets namely electricity consumption dataset and exchange-rate dataset. The results of the experiments demonstrate the remarkable performance of our model as well as the successful application of our proposed framework.