Dominik Janzing

Jan Lemeire, Dominik Janzing: Replacing Causal Faithfulness with Algorithmic Independence of Conditionals. Minds and Machines 23(2): 227-249 (2013)

Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf: From Ordinary Differential Equations to Structural Causal Models: the deterministic case. CoRR abs/1304.7920 (2013)

Dominik Janzing, Joris M. Mooij, Kun Zhang, Jan Lemeire, Jakob Zscheischler, Povilas Daniusis, Bastian Steudel, Bernhard Schölkopf: Information-geometric approach to inferring causal directions. Artif. Intell. 182-183: 1-31 (2012)

Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, Joris M. Mooij: On causal and anticausal learning. ICML 2012

Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf: Detecting low-complexity unobserved causes. CoRR abs/1202.3737 (2012)

Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf: Identifiability of Causal Graphs using Functional Models. CoRR abs/1202.3757 (2012)

Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Kernel-based Conditional Independence Test and Application in Causal Discovery. CoRR abs/1202.3775 (2012)

Jakob Zscheischler, Dominik Janzing, Kun Zhang: Testing whether linear equations are causal: A free probability theory approach. CoRR abs/1202.3779 (2012)

Povilas Daniusis, Dominik Janzing, Joris M. Mooij, Jakob Zscheischler, Bastian Steudel, Kun Zhang, Bernhard Schölkopf: Inferring deterministic causal relations. CoRR abs/1203.3475 (2012)

Kun Zhang, Bernhard Schölkopf, Dominik Janzing: Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery. CoRR abs/1203.3534 (2012)

Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf: Identifying confounders using additive noise models. CoRR abs/1205.2640 (2012)

Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Causal Inference on Time Series using Structural Equation Models. CoRR abs/1207.5136 (2012)

Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Causal Inference on Discrete Data Using Additive Noise Models. IEEE Trans. Pattern Anal. Mach. Intell. 33(12): 2436-2450 (2011)

Michel Besserve, Dominik Janzing, Nikos K. Logothetis, Bernhard Schölkopf: Finding dependencies between frequencies with the kernel cross-spectral density. ICASSP 2011: 2080-2083

Joris M. Mooij, Dominik Janzing, Tom Heskes, Bernhard Schölkopf: On Causal Discovery with Cyclic Additive Noise Models. NIPS 2011: 639-647

Dominik Janzing, Eleni Sgouritsa, Oliver Stegle, Jonas Peters, Bernhard Schölkopf: Detecting low-complexity unobserved causes. UAI 2011: 383-391

Jonas Peters, Joris M. Mooij, Dominik Janzing, Bernhard Schölkopf: Identifiability of Causal Graphs using Functional Models. UAI 2011: 589-598

Kun Zhang, Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Kernel-based Conditional Independence Test and Application in Causal Discovery. UAI 2011: 804-813

Jakob Zscheischler, Dominik Janzing, Kun Zhang: Testing whether linear equations are causal: A free probability theory approach. UAI 2011: 839-846

Bernhard Schölkopf, Dominik Janzing, Jonas Peters, Kun Zhang: Robust Learning via Cause-Effect Models. CoRR abs/1112.2738 (2011)

Isabelle Guyon, Dominik Janzing, Bernhard Schölkopf: Causality: Objectives and Assessment. Journal of Machine Learning Research - Proceedings Track 6: 1-42 (2010)

Joris M. Mooij, Dominik Janzing: Distinguishing between cause and effect. Journal of Machine Learning Research - Proceedings Track 6: 147-156 (2010)

Jonas Peters, Dominik Janzing, Bernhard Schölkopf: Identifying Cause and Effect on Discrete Data using Additive Noise Models. Journal of Machine Learning Research - Proceedings Track 9: 597-604 (2010)

Dominik Janzing, Bastian Steudel: Justifying Additive Noise Model-Based Causal Discovery via Algorithmic Information Theory. Open Syst. Inform. Dynam. 17(2): 189-212 (2010)

Dominik Janzing, Pawel Wocjan: A promiseBQP-complete string rewriting problem. Quantum Information & Computation 10(3&4): 234-257 (2010)

Dominik Janzing, Bernhard Schölkopf: Causal inference using the algorithmic Markov condition. IEEE Transactions on Information Theory 56(10): 5168-5194 (2010)

Bastian Steudel, Dominik Janzing, Bernhard Schölkopf: Causal Markov Condition for Submodular Information Measures. COLT 2010: 464-476

Dominik Janzing, Patrik O. Hoyer, Bernhard Schölkopf: Telling cause from effect based on high-dimensional observations. ICML 2010: 479-486

Joris M. Mooij, Oliver Stegle, Dominik Janzing, Kun Zhang, Bernhard Schölkopf: Probabilistic latent variable models for distinguishing between cause and effect. NIPS 2010: 1687-1695

Povilas Daniusis, Dominik Janzing, Joris M. Mooij, Jakob Zscheischler, Bastian Steudel, Kun Zhang, Bernhard Schölkopf: Inferring deterministic causal relations. UAI 2010: 143-150

Kun Zhang, Bernhard Schölkopf, Dominik Janzing: Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery. UAI 2010: 717-724

Bastian Steudel, Dominik Janzing, Bernhard Schölkopf: Causal Markov condition for submodular information measures. CoRR abs/1002.4020 (2010)

Dominik Janzing: Is there a physically universal cellular automaton or Hamiltonian? CoRR abs/1009.1720 (2010)

Joris M. Mooij, Dominik Janzing, Jonas Peters, Bernhard Schölkopf: Regression by dependence minimization and its application to causal inference in additive noise models. ICML 2009: 94

Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf: Detecting the direction of causal time series. ICML 2009: 101

Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf: Identifying confounders using additive noise models. UAI 2009: 249-257

Dominik Janzing, Bastian Steudel: Justifying additive-noise-model based causal discovery via algorithmic information theory. CoRR abs/0910.1691 (2009)

Dominik Janzing, Thomas Decker: How much is a quantum controller controlled by the controlled system? Appl. Algebra Eng. Commun. Comput. 19(3): 241-258 (2008)

Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf: Causal reasoning by evaluating the complexity of conditional densities with kernel methods. Neurocomputing 71(7-9): 1248-1256 (2008)

Pawel Wocjan, Dominik Janzing, Thomas Decker: Measuring 4-local qubit observables could probabilistically solve PSPACE. Quantum Information & Computation 8(8): 741-755 (2008)

Jonas Peters, Dominik Janzing, Arthur Gretton, Bernhard Schölkopf: Kernel Methods for Detecting the Direction of Time Series. GfKl 2008: 57-66

Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkopf: Nonlinear causal discovery with additive noise models. NIPS 2008: 689-696

Dominik Janzing, Bernhard Schölkopf: Causal inference using the algorithmic Markov condition. CoRR abs/0804.3678 (2008)

Dominik Janzing, Pawel Wocjan: A Simple PromiseBQP-complete Matrix Problem. Theory of Computing 3(1): 61-79 (2007)

Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf: Distinguishing between cause and effect via kernel-based complexity measures for conditional distributions. ESANN 2007: 441-446

Xiaohai Sun, Dominik Janzing: Learning causality by identifying common effects with kernel-based dependence measures. ESANN 2007: 453-458

Xiaohai Sun, Dominik Janzing: Exploring the causal order of binary variables via exponential hierarchies of Markov kernels. ESANN 2007: 465-470

Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf, Kenji Fukumizu: A kernel-based causal learning algorithm. ICML 2007: 855-862

Dominik Janzing: Computer science approach to quantum control. Univeristätsverlag Karlsruhe 2006, isbn 978-3-86644-083-8, pp. I-II, 1-137

Dominik Janzing, Jörn Müller-Quade: Guest editorial. Inform., Forsch. Entwickl. 21(1-2): 1-2 (2006)

Dominik Janzing: Quantum computing models as a tool box for controlling and understanding the nanoscopic world. Inform., Forsch. Entwickl. 21(1-2): 83-90 (2006)

Xiaohai Sun, Dominik Janzing, Bernhard Schölkopf: Causal Inference by Choosing Graphs with Most Plausible Markov Kernels. ISAIM 2006

Dominik Janzing: Über den Zusammenhang zwischen thermodynamisch reversiblem, kryptograpisch seitenkanalfreiem sowie quantenkohärentem Rechnen. GI Jahrestagung (1) 2005: 443

Dominik Janzing, Pawel Wocjan, Thomas Beth: On The Computational Power Of Physical Interactions: Bounds On The Number Of Time Steps For Simulating Arbitrary Interaction Graphs. Int. J. Found. Comput. Sci. 14(5): 889- (2003)

Pawel Wocjan, Dominik Janzing, Thomas Beth: Two QCMA-complete problems. Quantum Information & Computation 3(6): 635-643 (2003)

Dominik Janzing, Thomas Beth: Quasi-order of clocks and their synchronism and quantum bounds for copying timing information. IEEE Transactions on Information Theory 49(1): 230-240 (2003)

Dominik Janzing, Daniel Herrmann: Reliable and Efficient Inference of Bayesian Networks from Sparse Data by Statistical Learning Theory. CoRR cs.LG/0309015 (2003)

Pawel Wocjan, Dominik Janzing, Thomas Beth: Simulating arbitrary pair-interactions by a given Hamiltonian: graph-theoretical bounds on the time-complexity. Quantum Information & Computation 2(2): 117-132 (2002)

Pawel Wocjan, Martin Rötteler, Dominik Janzing, Thomas Beth: Universal simulation of Hamiltonians using a finite set of control operations. Quantum Information & Computation 2(2): 133-150 (2002)

Dominik Janzing, Thomas Beth: Quantum algorithm for measuring the eigenvalues of U ⊗ U^-1 for a black-box unitary transformation U. Quantum Information & Computation 2(3): 192-197 (2002)

Dominik Janzing: Quantum algorithm for measuring the energy of n qubits with unknown pair-interactions. Quantum Information & Computation 2(3): 198-207 (2002)

Pawel Wocjan, Dominik Janzing, Thomas Beth: Required sample size for learning sparse Bayesian networks with many variables. CoRR cs.LG/0204052 (2002)

Rainer Steinwandt, Dominik Janzing, Thomas Beth: On using quantum protocols to detect traffic analysis. Quantum Information & Computation 1(3): 62-69 (2001)

Pawel Wocjan, Dominik Janzing, Thomas Beth: Lower Bound on the Chromatic Number by Spectra of Weighted Adjacency Matrices. CoRR cs.DM/0112023 (2001)