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SIT (Signature-Informed Transformer For Asset Allocation)
Jupyter Notebook of code used in the numerics for the paper "A Kernel Two-Sample Test for Functional Data" by George Wynne and Andrew B. Duncan.
❗ This is a read-only mirror of the CRAN R package repository. SPORTSCausal — Spillover Time Series Causal Inference
Applied machine learning toolkit implementing Double Machine Learning for Energy Analytics.
Estimate collective causal influence among subsystems
AERCA: Root Cause Analysis of Anomalies in Multivariate Time Series through Granger Causal Discovery (ICLR 2025 Oral)
深度学习100例、深度学习DL、图片分类、目标识别、目标检测、自然语言处理nlp、文本分类、TensorFlow、PyTorch
A set of jupyter notebooks for the practice of TDA with the python Gudhi library together with popular machine learning and data sciences libraries.
Diachronic Embedding for Temporal Knowledge Graph Completion
Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).
Topics in Advanced Econometrics (ResEcon 703). University of Massachusetts Amherst. Taught by Matt Woerman
Weighted doubly robust learning for uplift modeling
Code for paper "Combining Doubly Robust Methods and Machine Learning for Estimating Average Treatment Effects for Observational Real-world Data"
Off-Policy Evaluation and Learning that is both Doubly Robust and Distributionally Robust.
A method for conditional shapley value estimation, built off the shapr package: https://github.com/NorskRegnesentral/shapr/tree/master
TensorFlow Implementation of "Enhanced Doubly Robust Learning for Debiasing Post-click Conversion Rate Estimation" in SIGIR'21
fuzzy average causal effects
A game theory approach to measuring spatial effects from machine learning models.
Deep Neural Networks for Options Pricing (Python) 💎
Gated Neural Network for Option Pricing implementation version Keras
Topological Graph Neural Networks (ICLR 2022)
A high-performance topological machine learning toolbox in Python
Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.