non-stationary

Code release for "Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting" (NeurIPS 2022), https://arxiv.org/abs/2205.14415

Code release for "Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors" (NeurIPS 2023), https://arxiv.org/abs/2305.18803

Comparative Genomics Toolkit 3

Gym environment for cooperative multi-agent reinforcement learning in heterogeneous robot teams

[KDD 2025] NILMFormer: A Sequence-To-Sequence Non-Stationarity Aware Transformer for Non-Intrusive Load Monitoring

Non-stationary spectral mixture kernels implemented in GPflow

Implementation for Non-stationary Spectral Kernels (NIPS 2017)

[ICDMW 2023] Python implementation of d_{symb}: "An Interpretable Distance Measure for Multivariate Non-Stationary Physiological Signals"

Forecasting in Non-stationary Environments with FuzzyTime Series

Multi-Objective Multi-Armed Bandit

An R package for fitting state-space models to repeated measures of multiple individuals with covariates

Tools for analyzing and generating non-Gaussian, non-stationary signals in engineering applications.

Forecast airline passenger demand using time series models like AR, ARMA, and LSTM to improve operations, optimize scheduling, enhance resource allocation, and streamline supply chain management through accurate demand predictions

This repository consists of codes that I developed for EEG and ECG signal processing

Probabilistic generation of hazard-consistent suites of fully non-stationary seismic records

Compared Non-stationary Multi-armed Bandits in Single-Agent to Multi-Agents Scenarios- Distributed Optimization and Learning(DOL) Course Project

End-to-End PyTorch implementation of Chang & Kim's (2026) iVDFM pipeline, Includes: amortized encoder, RegimeNet simplex embeddings, Laplace PriorNet, diagonal AR(p) companion-form dynamics, and injective MLP decoder. Trained via ELBO with reparameterized Laplace innovations. Benchmarked against iTransformer and TimeMixer baselines.

This repo is about forecasting the Yen movements in order to know whether to be long or short.

R function to implement Toda-Yamamoto Causality Test

time series analysis in R use cases