Causal Objective Function

Causal objective functions aim to identify and quantify the causal influence of specific variables or interventions on an outcome of interest, going beyond mere correlation. Current research focuses on developing algorithms and model architectures, such as residual neural networks and graph neural networks, to efficiently estimate these functions in complex dynamic systems, often leveraging techniques from causal inference and counterfactual analysis. This work is significant for improving the interpretability and reliability of machine learning models, particularly in applications where understanding causal relationships is crucial, such as root cause analysis in industrial processes or personalized medicine.

Papers

January 5, 2025

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations
Jiaping Wang, Simiao Zhang, Qiao-Chu He, Yifan Chen
Human Attention Pytorch Model Transformer Based Large Language Model Accurate Decoding Causal Attention CUDA Implementation Causal Objective Function

December 18, 2024

Discovering maximally consistent distribution of causal tournaments with Large Language Models
Federico Baldo, Simon Ferreira, Charles K. Assaad
Causal Discovery Causal Graph Causal Order Causal Ordering Causal Objective Function Causal Insight

December 6, 2024

Causal discovery with endogenous context variables
Wiebke Günther, Oana-Iuliana Popescu, Martin Rabel, Urmi Ninad, Andreas Gerhardus, Jakob Runge
Causal Discovery Causal Relation Global Endogenous Variate Causal Objective Function Constraint Based Causal Discovery

October 1, 2024

Inferring Kernel $ε$-Machines: Discovering Structure in Complex Systems
Alexandra M. Jurgens, Nicolas Brodu
Causal Effect Causal Structure Complex System Turing Machine Structure Discovery Bayesian Kernel Causal Objective Function

June 12, 2024

Counterfactual-based Root Cause Analysis for Dynamical Systems
Juliane Weilbach, Sebastian Gerwinn, Karim Barsim, Martin Fränzle
Causal Inference Dynamical System Root Cause Counterfactual Distribution Causal Objective Function

April 10, 2024

Causal Unit Selection using Tractable Arithmetic Circuits
Haiying Huang, Adnan Darwiche
Feature Selection Objective Function Basic UniT Causal Objective Function Arithmetic Circuit

January 5, 2024

Software Implementation of Digital Filtering via Tustin's Bilinear Transform
Connor W. Herron
Implementation Detail New Filtering Bilinear Matrix Inequality Causal Objective Function Filter Design

November 29, 2023

Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge
Xiaoge Zhang, Xiao-Lin Wang, Fenglei Fan, Yiu-Ming Cheung, Indranil Bose
Neural Network System Performance Causal Discovery Domain Knowledge Directed Acyclic Graph Causal Objective Function Causal Hierarchy Causality Based Learning

October 17, 2023

Causal Feature Selection via Transfer Entropy
Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli
Feature Selection Causal Discovery Causal Relationship Causal Objective Function Transfer Entropy

May 16, 2023

Dynamic Causal Explanation Based Diffusion-Variational Graph Neural Network for Spatio-temporal Forecasting
Guojun Liang, Prayag Tiwari, Sławomir Nowaczyk, Stefan Byttner, Fernando Alonso-Fernandez
Causal Graph Graph Neural Spatio Temporal Forecasting Causal Objective Function

February 28, 2023

An Algorithm and Complexity Results for Causal Unit Selection
Haiying Huang, Adnan Darwiche
Practical Algorithm Feature Selection Structural Causal Model Objective Function Causal Objective Function Complexity Result

February 3, 2023

Causal Confirmation Measures: From Simpson's Paradox to COVID-19
Chenguang Lu
Covid 19 Actual Cause Fermi Paradox Causal Objective Function

October 24, 2022

Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis
Luca Galimberti, Anastasis Kratsios, Giulia Livieri
Neural Network Case Relevance Neural Causal Model Deep Causal Causal Objective Function

May 24, 2022

Causal Influences Decouple From Their Underlying Network Structure In Echo State Networks
Kayson Fakhar, Fatemeh Hadaeghi, Claus C. Hilgetag
Brain Network Echo State Network Neural Circuit Neural Structure Causal Objective Function

February 20, 2022

Trying to Outrun Causality with Machine Learning: Limitations of Model Explainability Techniques for Identifying Predictive Variables
Matthew J. Vowels
Machine Learning Causal Structure Fundamental Limitation Causal Pattern Underlying Causal Explainability Technique Causal Objective Function