IEEE

IGES-RCI: Improved Greedy Equivalence Search and Recursive Causal Inference for Industrial Equipment Failure Prediction

Abstract: Predicting equipment failures plays a pivotal role in minimizing maintenance costs and boosting production efficiency within the industrial sector. This paper introduces a novel approach ...
IEEE

Causal Inference Via Style Bias Deconfounding for Domain Generalization

Abstract: Deep neural networks (DNNs) often struggle with out-of-distribution data, limiting their reliability in real-world visual applications. To address this issue, domain generalization methods ...
eLife

Correlation detection as a stimulus computable account for audiovisual perception, causal inference, and saliency maps in mammals

Animals excel at seamlessly integrating information from different senses, a capability critical for navigating complex environments. Despite recent progress in multisensory research, the absence of ...
ahajournals.org

Abstract 4368647: Improving Center Performance Assessment in Congenital Heart Surgery Through Causal Inference Weighting Approaches

Background: Traditional congenital heart surgery quality assessments rely on indirect standardization via regression, which can be complicated by heterogeneity in case-mix, surgical volume, and low ...
publichealth.jhu

The promise and pitfalls of integrating data for causal inference, with application to mental health treatment

Please join the Department of Epidemiology Center for Clinical Trials and Evidence Synthesis (CCTES) and Center for Drug Safety and Effectiveness (CDSE) in welcoming Elizabeth Stuart, PhD, AM, Chair ...
marktechpost

Meet oLLM: A Lightweight Python Library that brings 100K-Context LLM Inference to 8 GB Consumer GPUs via SSD Offload—No Quantization Required

oLLM is a lightweight Python library built on top of Huggingface Transformers and PyTorch and runs large-context Transformers on NVIDIA GPUs by aggressively offloading weights and KV-cache to fast ...
Frontiers

Correlation does not equal causation: the imperative of causal inference in machine learning models for immunotherapy

1 Department of Orthopedics, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China 2 Department of Pharmacy, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, ...
publichealth.jhu

Fundamentals of Causal Inference

Please join the JHU CFAR Biostatistics and Epidemiology Methodology (BEM) Core on Thursday, September 4, 2025, from 2-3 pm ET for a session covering the fundamentals of causal inference. If you have ...
Scientific Research Publishing

Varian, H.R. (2016) Causal Inference in Economics and Marketing. Proceedings of the National Academy of Sciences of the United States of America, 113, 7310-7315.

ABSTRACT: The study focuses on identifying and distinguishing whether there are differences between those students receiving special education services later compared to their general-education peers ...
Microsoft

Improving Generative Methods for Causal Evaluation via Simulation-Based Inference

Generating synthetic datasets that accurately reflect real-world observational data is critical for evaluating causal estimators, but remains a challenging task. Existing generative methods offer a ...