:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Machlanski, Damian, Samothrakis, Spyridon, Clarke, Paul
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Methodology
Online Access:	https://arxiv.org/abs/2310.18212
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Challenges of Hyperparameter Tuning for Accurate Causal Effect Estimation
by: Machlanski, Damian, et al.
Published: (2023)

Undersmoothing Causal Estimators with Generative Trees
by: Machlanski, Damian, et al.
Published: (2022)

Out-of-distribution generalisation is hard: evidence from ARC-like tasks
by: Dimitriadis, George, et al.
Published: (2025)

Games of Knightian Uncertainty as AGI testbeds
by: Samothrakis, Spyridon, et al.
Published: (2024)

Optimal Kernel Choice for Score Function-based Causal Discovery
by: Wang, Wenjie, et al.
Published: (2024)

Causal Ordering for Structure Learning from Time Series
by: Sanchez, Pedro P., et al.
Published: (2025)

Doubly Robust Proximal Causal Learning for Continuous Treatments
by: Wu, Yong, et al.
Published: (2023)

Causality-Inspired Robustness for Nonlinear Models via Representation Learning
by: Šola, Marin, et al.
Published: (2025)

Introducing Diminutive Causal Structure into Graph Representation Learning
by: Gao, Hang, et al.
Published: (2024)

Learning Causal Abstractions of Linear Structural Causal Models
by: Massidda, Riccardo, et al.
Published: (2024)

Multi-modal Causal Structure Learning and Root Cause Analysis
by: Zheng, Lecheng, et al.
Published: (2024)

Adjustment Identification Distance: A gadjid for Causal Structure Learning
by: Henckel, Leonard, et al.
Published: (2024)

Structure Maintained Representation Learning Neural Network for Causal Inference
by: Sun, Yang, et al.
Published: (2025)

An Algorithmic Approach for Causal Health Equity: A Look at Race Differentials in Intensive Care Unit (ICU) Outcomes
by: Plecko, Drago, et al.
Published: (2025)

Causal Contrastive Learning for Counterfactual Regression Over Time
by: Bouchattaoui, Mouad El, et al.
Published: (2024)

Causal Temporal Regime Structure Learning
by: Rahmani, Abdellah, et al.
Published: (2023)

A Unified Framework for Structure-Aware Clustering and Heterogeneous Causal Graph Learning
by: Du, Honglin, et al.
Published: (2026)

A Tutorial on Doubly Robust Learning for Causal Inference
by: Hlynsson, Hlynur Davíð
Published: (2024)

Double Machine Learning for Static Panel Data with Instrumental Variables: New Method and Applications
by: Baiardi, Anna, et al.
Published: (2026)

Multiply-Robust Causal Change Attribution
by: Quintas-Martinez, Victor, et al.
Published: (2024)

On Learning Causal Structures from Non-Experimental Data without Any Faithfulness Assumption
by: Lin, Hanti, et al.
Published: (2018)

Causal Interventional Prediction System for Robust and Explainable Effect Forecasting
by: Chu, Zhixuan, et al.
Published: (2024)

Minimum Specification Perturbation: Robustness as Distance-to-Falsification in Causal Inference
by: Dang, Hoang, et al.
Published: (2026)

Discrete Causal Representation Learning
by: Zhang, Wenjin, et al.
Published: (2026)

Structural Causality-based Generalizable Concept Discovery Models
by: Sinha, Sanchit, et al.
Published: (2024)

Forests for Differences: Robust Causal Inference Beyond Parametric DiD
by: Souto, Hugo Gobato, et al.
Published: (2025)

Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
by: Gamella, Juan L., et al.
Published: (2022)

Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selection
by: Zecchin, Matteo, et al.
Published: (2024)

Causal Flow-based Variational Auto-Encoder for Disentangled Causal Representation Learning
by: Fan, Di, et al.
Published: (2023)

Differentiable Structure Learning and Causal Discovery for General Binary Data
by: Deng, Chang, et al.
Published: (2025)

Doubly Robust Inference in Causal Latent Factor Models
by: Abadie, Alberto, et al.
Published: (2024)

Certified Causal Defense with Generalizable Robustness
by: Qiao, Yiran, et al.
Published: (2024)

Neural Networks Decoded: Targeted and Robust Analysis of Neural Network Decisions via Causal Explanations and Reasoning
by: Diallo, Alec F., et al.
Published: (2024)

Causal Decomposition Analysis with Synergistic Interventions: A Triply-Robust Machine Learning Approach to Addressing Multiple Dimensions of Social Disparities
by: Park, Soojin, et al.
Published: (2025)

CausalCompass: Evaluating the Robustness of Time-Series Causal Discovery in Misspecified Scenarios
by: Yi, Huiyang, et al.
Published: (2026)

DCILP: A Distributed Approach for Large-Scale Causal Structure Learning
by: Dong, Shuyu, et al.
Published: (2024)

Embracing Discrete Search: A Reasonable Approach to Causal Structure Learning
by: Wienöbst, Marcel, et al.
Published: (2025)

Improving Finite Sample Performance of Causal Discovery by Exploiting Temporal Structure
by: Bang, Christine W, et al.
Published: (2024)

Causal Discovery in Structural VAR Models Under Equal Noise Variance
by: HasanAbadi, SeyedSina Seyedi, et al.
Published: (2026)

Selective Induction Heads: How Transformers Select Causal Structures In Context
by: D'Angelo, Francesco, et al.
Published: (2025)