CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery

3 October 2023

Papers citing "CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery"

21 / 21 papers shown

Title
CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models Benjamin Herdeanu Juan Nathaniel Carla Roesch Jatan Buch Gregor Ramien Johannes Haux Pierre Gentine CML AI4CE 90 0 0 22 May 2025
Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery Rebecca Herman Jonas Wahl Urmi Ninad Jakob Runge 115 1 0 21 Mar 2025
GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality Zehao Liu Mengzhou Gao Pengfei Jiao CML AI4TS 79 3 0 23 Jan 2025
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data Yue Cheng Jiajun Zhang Weiwei Xing Xiaoyu Guo Yue Cheng Witold Pedrycz CML 116 0 0 25 Oct 2024
CUTS: Neural Causal Discovery from Irregular Time-Series Data Yuxiao Cheng Runzhao Yang Tingxiong Xiao Zongren Li J. Suo K. He Qionghai Dai OOD BDL AI4TS CML 68 28 0 15 Feb 2023
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise Wenbo Gong Joel Jennings Chen Zhang Nick Pawlowski AI4TS CML 60 26 0 26 Oct 2022
Efficient Neural Causal Discovery without Acyclicity Constraints Phillip Lippe Taco S. Cohen E. Gavves CML 57 72 0 22 Jul 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 115 303 0 03 Mar 2021
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To Game Alexander G. Reisach C. Seiler S. Weichwald CML 68 142 0 26 Feb 2021
High-recall causal discovery for autocorrelated time series with latent confounders Andreas Gerhardus J. Runge CML AI4TS 59 102 0 03 Jul 2020
Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data Sindy Löwe David Madras R. Zemel Max Welling CML BDL AI4TS 100 131 0 18 Jun 2020
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets Jakob Runge 69 193 0 07 Mar 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 209 1,713 0 05 Dec 2019
Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality Saurabh Khanna Vincent Y. F. Tan AI4TS 62 72 0 22 Nov 2019
Graph WaveNet for Deep Spatial-Temporal Graph Modeling Zonghan Wu Shirui Pan Guodong Long Jing Jiang Chengqi Zhang GNN AI4TS 92 2,176 0 31 May 2019
GRATIS: GeneRAting TIme Series with diverse and controllable characteristics Yanfei Kang Rob J. Hyndman Feng Li AI4TS 65 106 0 07 Mar 2019
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs Cristóbal Esteban Stephanie L. Hyland Gunnar Rätsch GAN SyDa MedIm 112 791 0 08 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,018 0 22 May 2017
Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks Samy Bengio Oriol Vinyals Navdeep Jaitly Noam M. Shazeer 152 2,038 0 09 Jun 2015
Learning Bayesian Networks with the bnlearn R Package M. Scutari BDL 174 1,736 0 26 Aug 2009
A Kernel Method for the Two-Sample Problem Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alex Smola 235 2,365 0 15 May 2008