GitHub

High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching (AISTATS 2025)

Official Python implementation of the paper High-Dimensional Differential Parameter Inference in Exponential Family using Time Score Matching, published at AISTATS 2025. In this paper, we introduce a ...
GitHub

exponential_moving_average.py

Exponential moving average is used in finance to analyze changes stock prices. EMA is used in conjunction with Simple moving average (SMA), EMA reacts to the changes in the value quicker than SMA, ...
IEEE

PyMEF — A framework for exponential families in Python

Abstract: Modeling data is often a critical step in many challenging applications in computer vision, bioinformatics or machine learning. Gaussian Mixture Models are a popular choice in many ...
Analytics India Magazine

Hands-On Guide to Time Series Analysis using Simple Exponential Smoothing in Python

Time series analysis involves studying datasets over time to identify patterns for predicting future values. Common applications of time series include stock prices, machinery depreciation, and ...