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A probabilistic model describes a system in its observational state.
Contribution to the theory of periodic reactions
A. J. Lotka · 1909
Earlier work this paper cites.
Die Kinetik der Invertinwirkung
L. Michaelis and M. L. Menten · 1913
Earlier work this paper cites.
Correlation and causation
S. Wright · 1921
Earlier work this paper cites.
The probability approach in econometrics
T. Haavelmo · 1944
Earlier work this paper cites.
The theory of prediction
N. Wiener · 1956
Earlier work this paper cites.
Investigating causal relations by econometric models and cross-spectral methods
C. W. J. Granger · 1969
Earlier work this paper cites.
Composable Markov processes
T. Schweder · 1970
Earlier work this paper cites.
Nonlinear Parameter Estimation
Y. Bard · 1974
Earlier work this paper cites.
Parameter fitting in dynamic models
M. Benson · 1979
Earlier work this paper cites.
A spline least squares method for numerical parameter estimation in differential equations
J. M. Varah · 1982
Earlier work this paper cites.
Autonomy
J. Aldrich · 1989
Earlier work this paper cites.
Structural Equations with Latent Variables
K. A. Bollen · 1989
Earlier work this paper cites.
The logic of causal inference
K. D. Hoover · 1990
Earlier work this paper cites.
Equivalence and synthesis of causal models
T. Verma and J. Pearl · 1991
Earlier work this paper cites.
Process dynamics, modeling, and control , volume 1
B. Ogunnaike and W. Ray · 1994
Earlier work this paper cites.
Graphical Models
S. Lauritzen · 1996
Earlier work this paper cites.
Causal inference from complex longitudinal data
J. M. Robins · 1997
Earlier work this paper cites.
Modeling gene expression with differential equations
T. Chen, H. He, and G. Church · 1999
Earlier work this paper cites.
Graphical Models for Event History Analysis based on Local Independence
V. Didelez · 2000
Earlier work this paper cites.
Measuring information transfer
T. Schreiber · 2000
Earlier work this paper cites.
Causation, Prediction, and Search
P. Spirtes, C. Glymour, and R. Scheines · 2000
Earlier work this paper cites.
Ancestral graph Markov models
T. Richardson and P. Spirtes · 2002
Earlier work this paper cites.
Dynamic causal modelling
K. Friston, L. Harrison, and W. Penny · 2003
Earlier work this paper cites.
Differential equations, bifurcations, and chaos in economics , volume 68
W-B. Zhang · 2005
Earlier work this paper cites.
Measurement Error in Nonlinear Models: A Modern Perspective
R. J. Carroll, D. Ruppert, L. A. Stefanski, and C. M. Crainiceanu · 2006
Earlier work this paper cites.
Instruments for causal inference: An epidemiologist’s dream?
M. A. Hernán and J. M. Robins · 2006
Earlier work this paper cites.
Learning the structure of linear latent variable models
R. Silva, R. Scheines, C. Glymour, and P. Spirtes · 2006
Cited alongside, same era.
Stochastic modelling for systems biology
D. J. Wilkinson · 2006
Cited alongside, same era.
New Introduction to Multiple Time Series Analysis
H. Lütkepohl · 2007
Cited alongside, same era.
Parameter estimation for differential equations: a generalized smoothing approach
J. O. Ramsay, G. Hooker, D. Campbell, and J. Cao · 2007
Cited alongside, same era.
Survival and Event History Analysis: A Process Point of View
O. Aalen, O. Borgan, and H. Gjessing · 2008
Cited alongside, same era.
Graphical models for marked point processes based on local independence
V. Didelez · 2008
Cited alongside, same era.
Causal inference and the data-fusion problem
E. Bareinboim and J. Pearl · 2016
Later among the works it cites.
The arrow of time in multivariate time series
Stefan Bauer, Bernhard Schölkopf, and Jonas Peters · 2016
Later among the works it cites.
Theoretical aspects of cyclic structural causal models
S. Bongers, J. Peters, B. Schölkopf, and J. M. Mooij · 2016
Later among the works it cites.
Methods for causal inference from gene perturbation experiments and validation
N. Meinshausen, A. Hauser, J. Mooij, J. Peters, P. Versteeg, and P. Bühlmann · 2016
Later among the works it cites.
Causal inference using invariant prediction: identification and confidence intervals
J. Peters, P. Bühlmann, and N. Meinshausen · 2016
Later among the works it cites.
Efficient and flexible inference for stochastic systems
S. Bauer, N. Gorbach, D. Miladinovic, and J. M. Buhmann · 2017
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B. Calderhead, M. Girolami, and N. D. Lawrence · 2009
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Causality: Models, Reasoning, and Inference
J. Pearl · 2009
Cited alongside, same era.
Detecting the direction of causal time series
J. Peters, D. Janzing, A. Gretton, and B. Schölkopf · 2009
Cited alongside, same era.
Granger causality and dynamic structural systems
H. White and X. Lu · 2010
Cited alongside, same era.
Learning linear cyclic causal models with latent variables
A. Hyttinen, F. Eberhardt, and P. O. Hoyer · 2012
Cited alongside, same era.
On causal and anticausal learning
B. Schölkopf, D. Janzing, J. Peters, E. Sgouritsa, K. Zhang, and J. M. Mooij · 2012
Cited alongside, same era.
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Random ordinary differential equations and their numerical solution
X. Han and P. E. Kloeden · 2017
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Learning large scale ordinary differential equation systems
F. V. Mikkelsen and N. R. Hansen · 2017
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Elements of Causal Inference: Foundations and Learning Algorithms
J. Peters, D. Janzing, and B. Schölkopf · 2017
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Nested Markov properties for acyclic directed mixed graphs
T. Richardson, R. J. Evans, J. M. Robins, and I. Shpitser · 2017
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Generalized structural causal models
T. Blom and J. M. Mooij · 2018
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From random differential equations to structural causal models: the stochastic case
S. Bongers and J. M. Mooij · 2018
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Domain adaptation by using causal inference to predict invariant conditional distributions
S. Magliacane, T. van Ommen, T. Claassen, S. Bongers, P. Versteeg, and J. M. Mooij · 2018
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Causal learning for partially observed stochastic dynamical systems
S. W. Mogensen, D. Malinsky, and N. R. Hansen · 2018
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Causal transfer in machine learning
M. Rojas-Carulla, B. Schölkopf, R. Turner, and J. Peters · 2018
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Anchor regression: heterogeneous data meets causality
D. Rothenhäusler, P. Bühlmann, N. Meinshausen, and J. Peters · 2018
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From deterministic ODEs to dynamic structural causal models
P. Rubenstein, S. Bongers, J. M. Mooij, and B. Schölkopf · 2018
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Identification in graphical causal models
I. Shpitser · 2018
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Causal discovery with linear non-Gaussian models under measurement error: Structural identifiability results
K. Zhang, M. Gong, J. Ramsey, K. Batmanghelich, P. Spirtes, and C. Glymour · 2018
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AReS and MaRS – adversarial and MMD-minimizing regression for SDEs
G. Abbati, P. Wenk, S. Bauer, M. A. Osborne, A. Krause, and B. Schölkopf · 2019
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Markov equivalence of marginalized local independence graphs
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Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs
P. Wenk, A. Gotovos, S. Bauer, N. Gorbach, A. Krause, and J. M. Buhmann · 2019
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Three principles of data science: predictability, computability, and stability (pcs)
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