Lower Bound on the Chromatic Number by Spectra of Weighted Adjacency Matrices - Pawel Wocjan; Dominik Janzing; Thomas Beth (CoRR, 2001)

On using quantum protocols to detect traffic analysis. - Rainer Steinwandt; Dominik Janzing; Thomas Beth (Quantum Inf. Comput., 2001)

Required sample size for learning sparse Bayesian networks with many variables - Pawel Wocjan; Dominik Janzing; Thomas Beth (CoRR, 2002)

Quantum algorithm for measuring the energy of n qubits with unknown pair-interactions. - Dominik Janzing (Quantum Inf. Comput., 2002)

Quantum algorithm for measuring the eigenvalues of U ⊗ U-1 for a black-box unitary transformation U. - Dominik Janzing; Thomas Beth (Quantum Inf. Comput., 2002)

Simulating arbitrary pair-interactions by a given Hamiltonian: graph-theoretical bounds on the time-complexity. - Pawel Wocjan; Dominik Janzing; Thomas Beth (Quantum Inf. Comput., 2002)

Universal simulation of Hamiltonians using a finite set of control operations. - Pawel Wocjan; Martin Rötteler; Dominik Janzing; Thomas Beth (Quantum Inf. Comput., 2002)

Reliable and Efficient Inference of Bayesian Networks from Sparse Data by Statistical Learning Theory - Dominik Janzing; Daniel Herrmann (CoRR, 2003)

On The Computational Power Of Physical Interactions: Bounds On The Number Of Time Steps For Simulating Arbitrary Interaction Graphs. - Dominik Janzing; Pawel Wocjan; Thomas Beth (Int. J. Found. Comput. Sci., 2003)

Two QCMA-complete problems. - Pawel Wocjan; Dominik Janzing; Thomas Beth (Quantum Inf. Comput., 2003)

Treating the Independent Set Problem by 2D Ising Interactions with Adiabatic Quantum Computing. - Pawel Wocjan; Dominik Janzing; Thomas Beth (Quantum Inf. Process., 2003)

Quasi-order of clocks and their synchronism and quantum bounds for copying timing information. - Dominik Janzing; Thomas Beth (IEEE Trans. Inf. Theory, 2003)

Über den Zusammenhang zwischen thermodynamisch reversiblem, kryptograpisch seitenkanalfreiem sowie quantenkohärentem Rechnen. - Dominik Janzing (GI Jahrestagung (1), 2005)

Ergodic Quantum Computing. - Dominik Janzing; Pawel Wocjan (Quantum Inf. Process., 2005)

Computer science approach to quantum control. - Dominik Janzing (Univeristätsverlag Karlsruhe, 2006)

Causal Inference by Choosing Graphs with Most Plausible Markov Kernels. - Xiaohai Sun; Dominik Janzing; Bernhard Schölkopf (AI&M, 2006)

Quantum computing models as a tool box for controlling and understanding the nanoscopic world. - Dominik Janzing (Inform. Forsch. Entwickl., 2006)

Guest editorial. - Dominik Janzing; Jörn Müller-Quade (Inform. Forsch. Entwickl., 2006)

Computer science approach to quantum control - Dominik Janzing (2006)

Learning causality by identifying common effects with kernel-based dependence measures. - Xiaohai Sun; Dominik Janzing (ESANN, 2007)

Exploring the causal order of binary variables via exponential hierarchies of Markov kernels. - Xiaohai Sun; Dominik Janzing (ESANN, 2007)

Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions. - Xiaohai Sun; Dominik Janzing; Bernhard Schölkopf (ESANN, 2007)

A kernel-based causal learning algorithm. - Xiaohai Sun; Dominik Janzing; Bernhard Schölkopf; Kenji Fukumizu (ICML, 2007)

A Simple PromiseBQP-complete Matrix Problem. - Dominik Janzing; Pawel Wocjan (Theory Comput., 2007)

Kernel Methods for Detecting the Direction of Time Series. - Jonas Peters; Dominik Janzing; Arthur Gretton; Bernhard Schölkopf (GfKl, 2008)

Nonlinear causal discovery with additive noise models. - Patrik O. Hoyer; Dominik Janzing; Joris M. Mooij; Jonas Peters; Bernhard Schölkopf (NIPS, 2008)

How much is a quantum controller controlled by the controlled system? - Dominik Janzing; Thomas Decker 002 (Appl. Algebra Eng. Commun. Comput., 2008)

Causal reasoning by evaluating the complexity of conditional densities with kernel methods. - Xiaohai Sun; Dominik Janzing; Bernhard Schölkopf (Neurocomputing, 2008)

Measuring 4-local qubit observables could probabilistically solve PSPACE. - Pawel Wocjan; Dominik Janzing; Thomas Decker 002 (Quantum Inf. Comput., 2008)

Entropy of Entanglement. - Dominik Janzing (Compendium of Quantum Physics, 2009)

Quantum Entropy. - Dominik Janzing (Compendium of Quantum Physics, 2009)

09401 Abstracts Collection - Machine learning approaches to statistical dependences and causality. - Dominik Janzing; Steffen L. Lauritzen; Bernhard Schölkopf (Machine learning approaches to statistical dependences and causality, 2009)

Regression by dependence minimization and its application to causal inference in additive noise models. - Joris M. Mooij; Dominik Janzing; Jonas Peters; Bernhard Schölkopf (ICML, 2009)

Detecting the direction of causal time series. - Jonas Peters; Dominik Janzing; Arthur Gretton; Bernhard Schölkopf (ICML, 2009)

Identifying confounders using additive noise models. - Dominik Janzing; Jonas Peters; Joris M. Mooij; Bernhard Schölkopf (UAI, 2009)

Causal Markov Condition for Submodular Information Measures. - Bastian Steudel; Dominik Janzing; Bernhard Schölkopf (COLT, 2010)

Telling cause from effect based on high-dimensional observations. - Dominik Janzing; Patrik O. Hoyer; Bernhard Schölkopf (ICML, 2010)

Probabilistic latent variable models for distinguishing between cause and effect. - Joris M. Mooij; Oliver Stegle; Dominik Janzing; Kun Zhang 001; Bernhard Schölkopf (NIPS, 2010)

Inferring deterministic causal relations. - Povilas Daniusis; Dominik Janzing; Joris M. Mooij; Jakob Zscheischler; Bastian Steudel; Kun Zhang 001; Bernhard Schölkopf (UAI, 2010)

Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery. - Kun Zhang 001; Bernhard Schölkopf; Dominik Janzing (UAI, 2010)

Is there a physically universal cellular automaton or Hamiltonian? - Dominik Janzing (CoRR, 2010)

Causality: Objectives and Assessment. - Isabelle Guyon; Dominik Janzing; Bernhard Schölkopf (NIPS Causality: Objectives and Assessment, 2010)

Distinguishing between cause and effect. - Joris M. Mooij; Dominik Janzing (NIPS Causality: Objectives and Assessment, 2010)

Identifying Cause and Effect on Discrete Data using Additive Noise Models. - Jonas Peters; Dominik Janzing; Bernhard Schölkopf (AISTATS, 2010)

Justifying Additive Noise Model-Based Causal Discovery via Algorithmic Information Theory. - Dominik Janzing; Bastian Steudel (Open Syst. Inf. Dyn., 2010)

A promiseBQP-complete string rewriting problem. - Dominik Janzing; Pawel Wocjan (Quantum Inf. Comput., 2010)

Causal inference using the algorithmic Markov condition. - Dominik Janzing; Bernhard Schölkopf (IEEE Trans. Inf. Theory, 2010)

Finding dependencies between frequencies with the kernel cross-spectral density. - Michel Besserve; Dominik Janzing; Nikos K. Logothetis; Bernhard Schölkopf (ICASSP, 2011)

On Causal Discovery with Cyclic Additive Noise Models. - Joris M. Mooij; Dominik Janzing; Tom Heskes; Bernhard Schölkopf (NIPS, 2011)

Detecting low-complexity unobserved causes. - Dominik Janzing; Eleni Sgouritsa; Oliver Stegle; Jonas Peters; Bernhard Schölkopf (UAI, 2011)

Identifiability of Causal Graphs using Functional Models. - Jonas Peters; Joris M. Mooij; Dominik Janzing; Bernhard Schölkopf (UAI, 2011)

Kernel-based Conditional Independence Test and Application in Causal Discovery. - Kun Zhang 001; Jonas Peters; Dominik Janzing; Bernhard Schölkopf (UAI, 2011)

Testing whether linear equations are causal: A free probability theory approach. - Jakob Zscheischler; Dominik Janzing; Kun Zhang 001 (UAI, 2011)

Robust Learning via Cause-Effect Models - Bernhard Schölkopf; Dominik Janzing; Jonas Peters; Kun Zhang 001 (CoRR, 2011)

Causal Inference on Discrete Data Using Additive Noise Models. - Jonas Peters; Dominik Janzing; Bernhard Schölkopf (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

On causal and anticausal learning. - Bernhard Schölkopf; Dominik Janzing; Jonas Peters; Eleni Sgouritsa; Kun Zhang 001; Joris M. Mooij (ICML, 2012)

Information-geometric approach to inferring causal directions. - Dominik Janzing; Joris M. Mooij; Kun Zhang 001; Jan Lemeire; Jakob Zscheischler; Povilas Daniusis; Bastian Steudel; Bernhard Schölkopf (Artif. Intell., 2012)

Causal Inference on Time Series using Structural Equation Models - Jonas Peters; Dominik Janzing; Bernhard Schölkopf (CoRR, 2012)

Semi-supervised Learning in Causal and Anticausal Settings. - Bernhard Schölkopf; Dominik Janzing; Jonas Peters; Eleni Sgouritsa; Kun Zhang 001; Joris M. Mooij (Empirical Inference, 2013)

Causal Inference on Time Series using Restricted Structural Equation Models. - Jonas Peters; Dominik Janzing; Bernhard Schölkopf (NIPS, 2013)

From Ordinary Differential Equations to Structural Causal Models: the deterministic case. - Joris M. Mooij; Dominik Janzing; Bernhard Schölkopf (UAI, 2013)

Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders. - Eleni Sgouritsa; Dominik Janzing; Jonas Peters; Bernhard Schölkopf (UAI, 2013)

Replacing Causal Faithfulness with Algorithmic Independence of Conditionals. - Jan Lemeire; Dominik Janzing (Minds Mach., 2013)

Consistency of Causal Inference under the Additive Noise Model. - Samory Kpotufe; Eleni Sgouritsa; Dominik Janzing; Bernhard Schölkopf (ICML, 2014)

Inferring latent structures via information inequalities. - Rafael Chaves; Lukas Luft; Thiago O. Maciel; David Gross 003; Dominik Janzing; Bernhard Schölkopf (UAI, 2014)

Estimating Causal Effects by Bounding Confounding. - Philipp Geiger; Dominik Janzing; Bernhard Schölkopf (UAI, 2014)

Inferring causal structure: a quantum advantage. - Katja Ried; Megan Agnew; Lydia Vermeyden; Dominik Janzing; Robert W. Spekkens; Kevin J. Resch (CoRR, 2014)

Causal discovery with continuous additive noise models. - Jonas Peters; Joris M. Mooij; Dominik Janzing; Bernhard Schölkopf (J. Mach. Learn. Res., 2014)

Inference of Cause and Effect with Unsupervised Inverse Regression. - Eleni Sgouritsa; Dominik Janzing; Philipp Hennig; Bernhard Schölkopf (AISTATS, 2015)

Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components. - Philipp Geiger; Kun Zhang 001; Bernhard Schölkopf; Mingming Gong; Dominik Janzing (ICML, 2015)

Removing systematic errors for exoplanet search via latent causes. - Bernhard Schölkopf; David W. Hogg; Dun Wang; Daniel Foreman-Mackey; Dominik Janzing; Carl-Johann Simon-Gabriel; Jonas Peters (ICML, 2015)

Telling cause from effect in deterministic linear dynamical systems. - Naji Shajarisales; Dominik Janzing; Bernhard Schölkopf; Michel Besserve (ICML, 2015)

Semi-supervised interpolation in an anticausal learning scenario. - Dominik Janzing; Bernhard Schölkopf (J. Mach. Learn. Res., 2015)

Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks. - Joris M. Mooij; Jonas Peters; Dominik Janzing; Jakob Zscheischler; Bernhard Schölkopf (J. Mach. Learn. Res., 2016)

Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach. - Moritz Grosse-Wentrup; Dominik Janzing; Markus Siegel; Bernhard Schölkopf (NeuroImage, 2016)

Modeling confounding by half-sibling regression. - Bernhard Schölkopf; David W. Hogg; Dun Wang; Daniel Foreman-Mackey; Dominik Janzing; Carl-Johann Simon-Gabriel; Jonas Peters (Proc. Natl. Acad. Sci. USA, 2016)

Avoiding Discrimination through Causal Reasoning. - Niki Kilbertus; Mateo Rojas-Carulla; Giambattista Parascandolo; Moritz Hardt; Dominik Janzing; Bernhard Schölkopf (NIPS, 2017)

Causal Consistency of Structural Equation Models. - Paul K. Rubenstein; Sebastian Weichwald; Stephan Bongers; Joris M. Mooij; Dominik Janzing; Moritz Grosse-Wentrup; Bernhard Schölkopf (UAI, 2017)

Group invariance principles for causal generative models. - Michel Besserve; Naji Shajarisales; Bernhard Schölkopf; Dominik Janzing (AISTATS, 2018)

Cause-Effect Inference by Comparing Regression Errors. - Patrick Blöbaum; Dominik Janzing; Takashi Washio; Shohei Shimizu; Bernhard Schölkopf (AISTATS, 2018)

Detecting non-causal artifacts in multivariate linear regression models. - Dominik Janzing; Bernhard Schölkopf (ICML, 2018)

Analysis of Cause-Effect Inference via Regression Errors. - Patrick Blöbaum; Dominik Janzing; Takashi Washio; Shohei Shimizu; Bernhard Schölkopf (CoRR, 2018)

Does Universal Controllability of Physical Systems Prohibit Thermodynamic Cycles? - Dominik Janzing; Pawel Wocjan (Open Syst. Inf. Dyn., 2018)

The Cause-Effect Problem: Motivation, Ideas, and Popular Misconceptions. - Dominik Janzing (Cause Effect Pairs in Machine Learning, 2019)

Causal Regularization. - Dominik Janzing (NeurIPS, 2019)

Selecting causal brain features with a single conditional independence test per feature. - Atalanti-Anastasia Mastakouri; Bernhard Schölkopf; Dominik Janzing (NeurIPS, 2019)

Perceiving the arrow of time in autoregressive motion. - Kristof Meding; Dominik Janzing; Bernhard Schölkopf; Felix A. Wichmann (NeurIPS, 2019)

Feature relevance quantification in explainable AI: A causality problem. - Dominik Janzing; Lenon Minorics; Patrick Blöbaum (CoRR, 2019)

Analysis of cause-effect inference by comparing regression errors. - Patrick Blöbaum; Dominik Janzing; Takashi Washio; Shohei Shimizu; Bernhard Schölkopf (PeerJ Comput. Sci., 2019)

Feature relevance quantification in explainable AI: A causal problem. - Dominik Janzing; Lenon Minorics; Patrick Blöbaum (AISTATS, 2020)

Quantifying causal contribution via structure preserving interventions. - Dominik Janzing; Patrick Blöbaum; Lenon Minorics (CoRR, 2020)

A Theory of Independent Mechanisms for Extrapolation in Generative Models. - Michel Besserve; Rémy Sun; Dominik Janzing; Bernhard Schölkopf (AAAI, 2021)

Why did the distribution change? - Kailash Budhathoki; Dominik Janzing; Patrick Blöbaum; Hoiyi Ng (AISTATS, 2021)

Necessary and sufficient conditions for causal feature selection in time series with latent common causes. - Atalanti-Anastasia Mastakouri; Bernhard Schölkopf; Dominik Janzing (ICML, 2021)

Causal version of Principle of Insufficient Reason and MaxEnt. - Dominik Janzing (CoRR, 2021)

Causal Forecasting: Generalization Bounds for Autoregressive Models. - Leena C. Vankadara; Philipp Michael Faller; Lenon Minorics; Debarghya Ghoshdastidar; Dominik Janzing (CoRR, 2021)

Obtaining Causal Information by Merging Datasets with MAXENT. - Sergio Hernan Garrido Mejia; Elke Kirschbaum; Dominik Janzing (AISTATS, 2022)

Testing Granger Non-Causality in Panels with Cross-Sectional Dependencies. - Lenon Minorics; Ali Caner Türkmen; David Kernert; Patrick Blöbaum; Laurent Callot; Dominik Janzing (AISTATS, 2022)

Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations. - Michel Besserve; Naji Shajarisales; Dominik Janzing; Bernhard Schölkopf (CLeaR, 2022)

You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction. - Osama Makansi; Julius von Kügelgen; Francesco Locatello; Peter Vincent Gehler; Dominik Janzing; Thomas Brox; Bernhard Schölkopf (ICLR, 2022)

Causal structure-based root cause analysis of outliers. - Kailash Budhathoki; Lenon Minorics; Patrick Blöbaum; Dominik Janzing (ICML, 2022)

Causal Inference Through the Structural Causal Marginal Problem. - Luigi Gresele; Julius von Kügelgen; Jonas M. Kübler; Elke Kirschbaum; Bernhard Schölkopf; Dominik Janzing (ICML, 2022)

On Measuring Causal Contributions via do-interventions. - Yonghan Jung; Shiva Prasad Kasiviswanathan; Jin Tian 001; Dominik Janzing; Patrick Blöbaum; Elias Bareinboim (ICML, 2022)

Score Matching Enables Causal Discovery of Nonlinear Additive Noise Models. - Paul Rolland; Volkan Cevher; Matthäus Kleindessner; Chris Russell 001; Dominik Janzing; Bernhard Schölkopf; Francesco Locatello (ICML, 2022)

Causal forecasting: generalization bounds for autoregressive models. - Leena Chennuru Vankadara; Philipp Michael Faller; Michaela Hardt; Lenon Minorics; Debarghya Ghoshdastidar; Dominik Janzing (UAI, 2022)

Correcting Confounding via Random Selection of Background Variables. - You-Lin Chen; Lenon Minorics; Dominik Janzing (CoRR, 2022)

Explaining the root causes of unit-level changes. - Kailash Budhathoki; George Michailidis; Dominik Janzing (CoRR, 2022)

Phenomenological Causality. - Dominik Janzing; Sergio Hernan Garrido Mejia (CoRR, 2022)

Assumption violations in causal discovery and the robustness of score matching. - Francesco Montagna; Atalanti-Anastasia Mastakouri; Elias Eulig; Nicoletta Noceti; Lorenzo Rosasco; Dominik Janzing; Bryon Aragam; Francesco Locatello (NeurIPS, 2023)

Causal information splitting: Engineering proxy features for robustness to distribution shifts. - Bijan Mazaheri; Atalanti-Anastasia Mastakouri; Dominik Janzing; Michaela Hardt (UAI, 2023)

Bounding probabilities of causation through the causal marginal problem. - Numair Sani; Atalanti-Anastasia Mastakouri; Dominik Janzing (CoRR, 2023)

Reinterpreting causal discovery as the task of predicting unobserved joint statistics. - Dominik Janzing; Philipp Michael Faller; Leena Chennuru Vankadara (CoRR, 2023)

Self-Compatibility: Evaluating Causal Discovery without Ground Truth. - Philipp Michael Faller; Leena C. Vankadara; Atalanti-Anastasia Mastakouri; Francesco Locatello; Dominik Janzing (AISTATS, 2024)

Quantifying intrinsic causal contributions via structure preserving interventions. - Dominik Janzing; Patrick Blöbaum; Atalanti-Anastasia Mastakouri; Philipp Michael Faller; Lenon Minorics; Kailash Budhathoki (AISTATS, 2024)

Meaningful Causal Aggregation and Paradoxical Confounding. - Yuchen Zhu; Kailash Budhathoki; Jonas M. Kübler; Dominik Janzing (CLeaR, 2024)

Causal vs. Anticausal merging of predictors. - Sergio Hernan Garrido Mejia; Patrick Blöbaum; Bernhard Schölkopf; Dominik Janzing (NeurIPS, 2024)

Multiply-Robust Causal Change Attribution. - Victor Quintas-Martinez; Mohammad Taha Bahadori; Eduardo Santiago; Jeff Mu; Dominik Janzing; David Heckerman (CoRR, 2024)

Root Cause Analysis of Outliers with Missing Structural Knowledge. - Nastaran Okati; Sergio Hernan Garrido Mejia; William Roy Orchard; Patrick Blöbaum; Dominik Janzing (CoRR, 2024)

DoWhy-GCM: An Extension of DoWhy for Causal Inference in Graphical Causal Models. - Patrick Blöbaum; Peter Götz; Kailash Budhathoki; Atalanti-Anastasia Mastakouri; Dominik Janzing (J. Mach. Learn. Res., 2024)

Toward Falsifying Causal Graphs Using a Permutation-Based Test. - Elias Eulig; Atalanti-Anastasia Mastakouri; Patrick Blöbaum; Michaela Hardt; Dominik Janzing (AAAI, 2025)

Cross-validating causal discovery via Leave-One-Variable-Out. - Daniela Schkoda; Philipp Michael Faller; Dominik Janzing; Patrick Blöbaum (CLeaR, 2025)

Toward Universal Laws of Outlier Propagation. - Aram Ebtekar; Yuhao Wang; Dominik Janzing (UAI, 2025)

On Different Notions of Redundancy in Conditional-Independence-Based Discovery of Graphical Models. - Philipp Michael Faller; Dominik Janzing (CoRR, 2025)