Cover Image

CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Stein, Gideon, Shadaydeh, Maha, Blunk, Jan, Penzel, Niklas, Denzler, Joachim
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

Group Interventions on Deep Networks for Causal Discovery in Subsystems
by: Ahmad, Wasim, et al.
Published: (2025)

TCD-Arena: Assessing Robustness of Time Series Causal Discovery Methods Against Assumption Violations
by: Stein, Gideon, et al.
Published: (2026)

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

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

Reducing Bias in Pre-trained Models by Tuning while Penalizing Change
by: Penzel, Niklas, et al.
Published: (2024)

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

Locally Explaining Prediction Behavior via Gradual Interventions and Measuring Property Gradients
by: Penzel, Niklas, et al.
Published: (2025)

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

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

When Medical Imaging Met Self-Attention: A Love Story That Didn't Quite Work Out
by: Piater, Tristan, et al.
Published: (2024)

Time series causal discovery with variable lags
by: Petrungaro, Bruno, et al.
Published: (2026)

Distance-informed Neural Processes
by: Venkataramanan, Aishwarya, et al.
Published: (2025)

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

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

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

Fiaingen: A financial time series generative method matching real-world data quality
by: Rožanec, Jože M., et al.
Published: (2025)

Facing Asymmetry -- Uncovering the Causal Link between Facial Symmetry and Expression Classifiers using Synthetic Interventions
by: Büchner, Tim, et al.
Published: (2024)

Robust agents learn causal world models
by: Richens, Jonathan, et al.
Published: (2024)

Score matching through the roof: linear, nonlinear, and latent variables causal discovery
by: Montagna, Francesco, et al.
Published: (2024)

Directionality of Interpersonal Neural Influence in Functional Near‐Infrared Spectroscopy Hyperscanning: Feasibility of Information–Theoretic Causality Analysis in Motor Tasks
by: Maha Shadaydeh, et al.
Published: (2025)

Quantum-enhanced causal discovery for a small number of samples
by: Terada, Yu, et al.
Published: (2025)

Scaling of learning time for high dimensional inputs
by: Brito, Carlos Stein
Published: (2026)

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

Learning Causally Invariant Reward Functions from Diverse Demonstrations
by: Ovinnikov, Ivan, et al.
Published: (2024)

CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models
by: Herdeanu, Benjamin, et al.
Published: (2025)

Recency Biased Causal Attention for Time-series Forecasting
by: Hegazy, Kareem, et al.
Published: (2025)

The Power of Properties: Uncovering the Influential Factors in Emotion Classification
by: Büchner, Tim, et al.
Published: (2024)

Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible?
by: Schur, Felix, et al.
Published: (2026)

The role of positional encodings in the ARC benchmark
by: Costa, Guilherme H. Bandeira, et al.
Published: (2025)

Recovering implicit physics model under real-world constraints
by: Banerjee, Ayan, et al.
Published: (2024)

Quantitative causality, causality-guided scientific discovery, and causal machine learning
by: Liang, X. San, et al.
Published: (2024)

How predictable is language model benchmark performance?
by: Owen, David
Published: (2024)

Learning-augmented robotic automation for real-world manufacturing
by: Kim, Yunho, et al.
Published: (2026)

Scaling-laws for Large Time-series Models
by: Edwards, Thomas D. P., et al.
Published: (2024)

Learning Causal Graphs at Scale: A Foundation Model Approach
by: Yin, Naiyu, et al.
Published: (2025)

Simulation-based reinforcement learning for real-world autonomous driving
by: Osiński, Błażej, et al.
Published: (2019)

Merging Text Transformer Models from Different Initializations
by: Verma, Neha, et al.
Published: (2024)

Auxiliary task discovery through generate-and-test
by: Rafiee, Banafsheh, et al.
Published: (2022)