links to conference publications in graph-based deep learning

Code for Pesaran, Pick and Timmermann "Forecasting with panel data: Estimation uncertainty versus parameter heterogeneity"

Financial Econometrics data warpper package

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

R wrapper for nowcast_lstm Python library. Long short-term memory neural networks for economic nowcasting.

LSTM neural networks for nowcasting economic data.

[Advanced] Practical Statistical Inference and Machine/Deep Learning for Time Series Forecasting

Network Regressions in Stata

Based on the approaches which are presented in "Forecasting Realised Volatility: Does the LASSO approach outperform HAR?" (Yi Ding, Dimos Kambouroudis & David G McMillan, 2021) I predict realized v…

This resposity is a pre-released verison of Python code used in the paper "Asset pricing via the conditional quantile variational autoencoder".

matlab toolboxes

Econometrics lecture notes with examples using the Julia language

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

A Python 3.7 package for the econometric analysis of networks

MATLAB wrapper for nowcast_lstm python package

An R Package for Change Point Localisation

Bayesian Learning course at Stockholm University

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

A curated list of awesome network analysis resources.

Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - focus on uncertainty quantification

volatility forecasting within the synthetic prediction framework