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CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models

CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models

22 May 2025
Benjamin Herdeanu
Juan Nathaniel
Carla Roesch
Jatan Buch
Gregor Ramien
Johannes Haux
Pierre Gentine
    CMLAI4CE
ArXiv (abs)PDFHTML

Papers citing "CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models"

36 / 36 papers shown
Title
Deep Koopman operator framework for causal discovery in nonlinear dynamical systems
Deep Koopman operator framework for causal discovery in nonlinear dynamical systems
Juan Nathaniel
Carla Roesch
Jatan Buch
Derek DeSantis
Adam Rupe
Kara Lamb
Pierre Gentine
CML
62
1
0
20 May 2025
Generative emulation of chaotic dynamics with coherent prior
Generative emulation of chaotic dynamics with coherent prior
Juan Nathaniel
Pierre Gentine
AI4TSAI4CE
62
3
0
19 Apr 2025
Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery
Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery
Rebecca Herman
Jonas Wahl
Urmi Ninad
Jakob Runge
146
1
0
21 Mar 2025
CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series
CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series
Gideon Stein
M. Shadaydeh
Jan Blunk
Niklas Penzel
Joachim Denzler
AI4TS
78
1
0
21 Mar 2025
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
P. Brouillard
Chandler Squires
Jonas Wahl
Konrad P. Kording
Karen Sachs
Alexandre Drouin
Dhanya Sridhar
CML
134
3
0
02 Dec 2024
Tangent Space Causal Inference: Leveraging Vector Fields for Causal
  Discovery in Dynamical Systems
Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical Systems
Kurt Butler
Daniel Waxman
Petar M. Djurić
CML
63
2
0
30 Oct 2024
Standardizing Structural Causal Models
Standardizing Structural Causal Models
Weronika Ormaniec
Scott Sussex
Lars Lorch
Bernhard Schölkopf
Andreas Krause
CML
143
7
0
17 Jun 2024
Dynamic Structural Causal Models
Dynamic Structural Causal Models
Philip A. Boeken
Joris M. Mooij
112
4
0
03 Jun 2024
ChaosBench: A Multi-Channel, Physics-Based Benchmark for
  Subseasonal-to-Seasonal Climate Prediction
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction
Juan Nathaniel
Yongquan Qu
Tung Nguyen
Sungduk Yu
Julius J. M. Busecke
Aditya Grover
Pierre Gentine
AI4ClAI4TS
124
18
0
01 Feb 2024
Neural General Circulation Models for Weather and Climate
Neural General Circulation Models for Weather and Climate
Dmitrii Kochkov
J. Yuval
I. Langmore
Peter C. Norgaard
Jamie A. Smith
...
Peter W. Battaglia
Alvaro Sanchez-Gonzalez
Matthew Willson
Michael P. Brenner
Stephan Hoyer
AI4ClAI4CE
131
169
0
13 Nov 2023
CausalTime: Realistically Generated Time-series for Benchmarking of
  Causal Discovery
CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery
Yuxiao Cheng
Ziqian Wang
Tingxiong Xiao
Qin Zhong
J. Suo
Kunlun He
AI4TSCML
91
17
0
03 Oct 2023
$\texttt{causalAssembly}$: Generating Realistic Production Data for
  Benchmarking Causal Discovery
causalAssembly\texttt{causalAssembly}causalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery
Konstantin Göbler
Tobias Windisch
Mathias Drton
T. Pychynski
Steffen Sonntag
Martin Roth
CML
183
13
0
19 Jun 2023
CUTS+: High-dimensional Causal Discovery from Irregular Time-series
CUTS+: High-dimensional Causal Discovery from Irregular Time-series
Yuxiao Cheng
Lianglong Li
Tingxiong Xiao
Zongren Li
Qionghai Dai
J. Suo
K. He
CMLBDLAI4TS
94
26
0
10 May 2023
A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive
  Noise Models
A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models
Alexander G. Reisach
Myriam Tami
C. Seiler
Antoine Chambaz
S. Weichwald
CML
101
21
0
31 Mar 2023
Model scale versus domain knowledge in statistical forecasting of
  chaotic systems
Model scale versus domain knowledge in statistical forecasting of chaotic systems
W. Gilpin
AI4TS
99
23
0
13 Mar 2023
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios
Luca Castri
Sariah Mghames
Marc Hanheide
Nicola Bellotto
CML
75
13
0
20 Feb 2023
CUTS: Neural Causal Discovery from Irregular Time-Series Data
CUTS: Neural Causal Discovery from Irregular Time-Series Data
Yuxiao Cheng
Runzhao Yang
Tingxiong Xiao
Zongren Li
J. Suo
K. He
Qionghai Dai
OODBDLAI4TSCML
73
28
0
15 Feb 2023
Causal discovery for time series with latent confounders
Causal discovery for time series with latent confounders
Christian Reiser
BDLCMLAI4TS
37
4
0
07 Sep 2022
TabPFN: A Transformer That Solves Small Tabular Classification Problems
  in a Second
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
Noah Hollmann
Samuel G. Müller
Katharina Eggensperger
Frank Hutter
119
317
0
05 Jul 2022
Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in
  the Southeast Pacific
Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific
Andrew Jesson
P. Manshausen
A. Douglas
D. Watson‐Parris
Y. Gal
P. Stier
AI4Cl
129
7
0
28 Oct 2021
Chaos as an interpretable benchmark for forecasting and data-driven
  modelling
Chaos as an interpretable benchmark for forecasting and data-driven modelling
W. Gilpin
AI4TS
65
82
0
11 Oct 2021
Neural graphical modelling in continuous-time: consistency guarantees
  and algorithms
Neural graphical modelling in continuous-time: consistency guarantees and algorithms
Alexis Bellot
K. Branson
M. Schaar
CMLAI4TS
91
46
0
06 May 2021
Data Generating Process to Evaluate Causal Discovery Techniques for Time
  Series Data
Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data
A. Lawrence
Marcus Kaiser
Rui Sampaio
Maksim Sipos
CMLAI4TS
109
20
0
16 Apr 2021
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To
  Game
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To Game
Alexander G. Reisach
C. Seiler
S. Weichwald
CML
82
142
0
26 Feb 2021
High-recall causal discovery for autocorrelated time series with latent
  confounders
High-recall causal discovery for autocorrelated time series with latent confounders
Andreas Gerhardus
J. Runge
CMLAI4TS
96
102
0
03 Jul 2020
Discovering contemporaneous and lagged causal relations in
  autocorrelated nonlinear time series datasets
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets
Jakob Runge
93
195
0
07 Mar 2020
DYNOTEARS: Structure Learning from Time-Series Data
DYNOTEARS: Structure Learning from Time-Series Data
Roxana Pamfil
Nisara Sriwattanaworachai
Shaan Desai
Philip Pilgerstorfer
Paul Beaumont
K. Georgatzis
Bryon Aragam
CMLAI4TSBDL
109
192
0
02 Feb 2020
Economy Statistical Recurrent Units For Inferring Nonlinear Granger
  Causality
Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality
Saurabh Khanna
Vincent Y. F. Tan
AI4TS
71
72
0
22 Nov 2019
Causal Modeling of Dynamical Systems
Causal Modeling of Dynamical Systems
Stephan Bongers
Tineke Blom
Joris M. Mooij
73
24
0
23 Mar 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning
DAGs with NO TEARS: Continuous Optimization for Structure Learning
Xun Zheng
Bryon Aragam
Pradeep Ravikumar
Eric Xing
NoLaCMLOffRL
109
951
0
04 Mar 2018
The History Began from AlexNet: A Comprehensive Survey on Deep Learning
  Approaches
The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches
Md. Zahangir Alom
T. Taha
C. Yakopcic
Stefan Westberg
P. Sidike
Mst Shamima Nasrin
B. Van Essen
A. Awwal
V. Asari
VLM
133
882
0
03 Mar 2018
Remote Sensing Image Scene Classification: Benchmark and State of the
  Art
Remote Sensing Image Scene Classification: Benchmark and State of the Art
Gong Cheng
Junwei Han
Xiaoqiang Lu
108
2,272
0
01 Mar 2017
From Deterministic ODEs to Dynamic Structural Causal Models
From Deterministic ODEs to Dynamic Structural Causal Models
Paul Kishan Rubenstein
Stephan Bongers
Bernhard Schölkopf
Joris M. Mooij
86
55
0
29 Aug 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.4K
195,003
0
10 Dec 2015
From Ordinary Differential Equations to Structural Causal Models: the
  deterministic case
From Ordinary Differential Equations to Structural Causal Models: the deterministic case
Joris Mooij
Dominik Janzing
Bernhard Schölkopf
126
105
0
09 Aug 2014
Structural Intervention Distance (SID) for Evaluating Causal Graphs
Structural Intervention Distance (SID) for Evaluating Causal Graphs
J. Peters
Peter Buhlmann
CML
104
40
0
05 Jun 2013
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