Copertina

Group Interventions on Deep Networks for Causal Discovery in Subsystems

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ahmad, Wasim, Denzler, Joachim, Shadaydeh, Maha
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Deep Learning-based Group Causal Inference in Multivariate Time-series
di: Ahmad, Wasim, et al.
Pubblicazione: (2024)

Embracing the black box: Heading towards foundation models for causal discovery from time series data
di: Stein, Gideon, et al.
Pubblicazione: (2024)

CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series
di: Stein, Gideon, et al.
Pubblicazione: (2025)

Regime Identification for Improving Causal Analysis in Non-stationary Timeseries
di: Ahmad, Wasim, et al.
Pubblicazione: (2024)

Mitigating Spurious Correlations in Patch-wise Tumor Classification on High-Resolution Multimodal Images
di: Asaad, Ihab, et al.
Pubblicazione: (2025)

Gradient Extrapolation for Debiased Representation Learning
di: Asaad, Ihab, et al.
Pubblicazione: (2025)

Distance-informed Neural Processes
di: Venkataramanan, Aishwarya, et al.
Pubblicazione: (2025)

Unraveling Anomalies in Time: Unsupervised Discovery and Isolation of Anomalous Behavior in Bio-regenerative Life Support System Telemetry
di: Rewicki, Ferdinand, et al.
Pubblicazione: (2024)

Anomalous Agreement: How to find the Ideal Number of Anomaly Classes in Correlated, Multivariate Time Series Data
di: Rewicki, Ferdinand, et al.
Pubblicazione: (2025)

Linear Causal Discovery with Interventional Constraints
di: Guo, Zhigao, et al.
Pubblicazione: (2025)

FastCAV: Efficient Computation of Concept Activation Vectors for Explaining Deep Neural Networks
di: Schmalwasser, Laines, et al.
Pubblicazione: (2025)

Modeling COVID-19 Dynamics in German States Using Physics-Informed Neural Networks
di: Rothenbeck, Phillip, et al.
Pubblicazione: (2025)

Causal Discovery by Interventions via Integer Programming
di: Elrefaey, Abdelmonem, et al.
Pubblicazione: (2024)

Regret-Based Federated Causal Discovery with Unknown Interventions
di: Baldo, Federico, et al.
Pubblicazione: (2025)

Interventional Causal Discovery in a Mixture of DAGs
di: Varıcı, Burak, et al.
Pubblicazione: (2024)

Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions
di: Okita, Tsuyoshi
Pubblicazione: (2026)

Causal Discovery in Action: Learning Chain-Reaction Mechanisms from Interventions
di: Panayiotou, Panayiotis, et al.
Pubblicazione: (2026)

Intervention and Conditioning in Causal Bayesian Networks
di: Galhotra, Sainyam, et al.
Pubblicazione: (2024)

Deep Causal Learning: Representation, Discovery and Inference
di: Deng, Zizhen, et al.
Pubblicazione: (2022)

Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery
di: Olko, Mateusz, et al.
Pubblicazione: (2022)

CAnDOIT: Causal Discovery with Observational and Interventional Data from Time-Series
di: Castri, Luca, et al.
Pubblicazione: (2024)

Physics Informed Modeling of Ecosystem Respiration via Dynamic Mode Decomposition with Control Input
di: Shadaydeh, Maha, et al.
Pubblicazione: (2024)

RealTCD: Temporal Causal Discovery from Interventional Data with Large Language Model
di: Li, Peiwen, et al.
Pubblicazione: (2024)

Local Causal Discovery for Statistically Efficient Causal Inference
di: Schubert, Mátyás, et al.
Pubblicazione: (2025)

Differentiable Constraint-Based Causal Discovery
di: Zhou, Jincheng, et al.
Pubblicazione: (2025)

Relational Causal Discovery with Latent Confounders
di: Negro, Matteo, et al.
Pubblicazione: (2025)

$χ$SPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains
di: Poonia, Harsh, et al.
Pubblicazione: (2024)

SCOPE: Sequential Causal Optimization of Process Interventions
di: De Moor, Jakob, et al.
Pubblicazione: (2025)

PACER: Acyclic Causal Discovery from Large-Scale Interventional Data
di: Torné, Ramon Viñas, et al.
Pubblicazione: (2026)

The Interaction Bottleneck of Deep Neural Networks: Discovery, Proof, and Modulation
di: Deng, Huiqi, et al.
Pubblicazione: (2025)

Multi-Domain Causal Discovery in Bijective Causal Models
di: Jalaldoust, Kasra, et al.
Pubblicazione: (2025)

Learning to Defer for Causal Discovery with Imperfect Experts
di: Clivio, Oscar, et al.
Pubblicazione: (2025)

Federated Causal Discovery from Heterogeneous Data
di: Li, Loka, et al.
Pubblicazione: (2024)

CauScale: Neural Causal Discovery at Scale
di: Peng, Bo, et al.
Pubblicazione: (2026)

Challenges and Considerations in the Evaluation of Bayesian Causal Discovery
di: Mamaghan, Amir Mohammad Karimi, et al.
Pubblicazione: (2024)

Mask2Cause: Causal Discovery via Adjacency Constrained Causal Attention
di: Muhammad, Omar, et al.
Pubblicazione: (2026)

CIVeX: Causal Intervention Verification for Language Agents
di: Rovai, Fabio
Pubblicazione: (2026)

Transferring Information Across Interventions in Causal Bayesian Optimization
di: Javidian, Mohammad Ali
Pubblicazione: (2026)

Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge
di: Zhang, Xiaoge, et al.
Pubblicazione: (2023)

Temporal Latent Variable Structural Causal Model for Causal Discovery under External Interferences
di: Cai, Ruichu, et al.
Pubblicazione: (2025)