Publications of D Janzing

Journal Article (11)

1.
Journal Article
Janzing, D.; Mooij, J.; Zhang, K.; Lemeire, J.; Zscheischler, J.; Daniušis, P.; Steudel, B.; Schölkopf, B.: Information-geometric approach to inferring causal directions. Artificial Intelligence 182-183, pp. 1 - 31 (2012)
2.
Journal Article
Peters, J.; Janzing, D.; Schölkopf, B.: Causal Inference on Discrete Data using Additive Noise Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (12), pp. 2436 - 2450 (2011)
3.
Journal Article
Allahverdyan, A.; Hovhannisyan , K.; Janzing, D.; Mahler, G.: Thermodynamic limits of dynamic cooling. Physical Review E 84 (4), 041109, pp. 1 - 16 (2011)
4.
Journal Article
Janzing, D.; Schölkopf, B.: Causal Inference Using the Algorithmic Markov Condition. IEEE Transactions on Information Theory 56 (10), pp. 5168 - 5194 (2010)
5.
Journal Article
Janzing, D.; Steudel, B.: Justifying Additive Noise Model-Based Causal Discovery via Algorithmic Information Theory. Open Systems and Information Dynamics 17 (2), pp. 189 - 212 (2010)
6.
Journal Article
Janzing, D.: On the Entropy Production of Time Series with Unidirectional Linearity. Journal of Statistical Physics 138 (4-5), pp. 767 - 779 (2010)
7.
Journal Article
Janzing, D.; Wocjan, P.: A promise BQP-complete string rewriting problem. Quantum Information and Computation 10 (3), pp. 234 - 257 (2010)
8.
Journal Article
Allahverdyan, A.; Janzing, D.; Mahler, G.: Thermodynamic efficiency of information and heat flow. Journal of Statistical Mechanics: Theory and Experiment 2009 (9), P09011, pp. 1 - 35 (2009)
9.
Journal Article
Janzing, D.; Wocjan, P.; Zhang, S.: A Single-shot Measurement of the Energy of Product States in a Translation Invariant Spin Chain Can Replace Any Quantum Computation. New Journal of Physics 10 (8), 093004, pp. 1 - 18 (2008)
10.
Journal Article
Allahverdyan, A.; Janzing, D.: Relating the Thermodynamic Arrow of Time to the Causal Arrow. Journal of Statistical Mechanics: Theory and Experiment 2008, P04001, pp. 1 - 21 (2008)
11.
Journal Article
Sun, X.; Janzing, D.; Schölkopf, B.: Causal Reasoning by Evaluating the Complexity of Conditional Densities with Kernel Methods. Neurocomputing 71 (7-9), pp. 1248 - 1256 (2008)

Proceedings (2)

12.
Proceedings
Causality: Objectives and Assessment. NIPS 2008 Workshop: Causality: Objectives and Assessment , Whistler, BC, Canada, December 12, 2008. (2010)
13.
Proceedings
Machine learning approaches to statistical dependences and causality (Dagstuhl Reports, 09401). Dagstuhl Seminar: Machine learning approaches to statistical dependences and causality , Schloss Dagstuhl, Germany, September 27, 2009 - October 02, 2009. (2009)

Conference Paper (28)

14.
Conference Paper
Besserve, M.; Shajarisales, N.; Janzing, D.; Schölkopf, B.: Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations. In: Proceedings of Machine Learning Research (PMLR), Vol. 177, pp. 110 - 143. 1st Conference on Causal Learning and Reasoning (CLeaR 2022), Eureka, CA, USA, April 11, 2022 - April 13, 2022. Curran, Red Hook, NY, USA (2022)
15.
Conference Paper
Besserve, M.; Sun, R.; Janzing, D.; Schölkopf, B.: A theory of independent mechanisms for extrapolation in generative models. In: Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 35, pp. 6741 - 6749. 35th AAAI Conference on Artificial Intelligence: A Virtual Conference, February 02, 2021 - February 09, 2021. (2021)
16.
Conference Paper
Besserve, M.; Shajarisales, N.; Schölkopf, B.; Janzing, D.: Group invariance principles for causal generative models. In: International Conference on Artificial Intelligence and Statistics, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands, pp. 557 - 565 (Eds. Storkey , A.; Perez-Cruz, F.). 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018), Playa Blanca, Spain, April 09, 2018 - April 11, 2018. International Machine Learning Society, Madison, WI, USA (2018)
17.
Conference Paper
Shajarisales, N.; Janzing, D.; Schölkopf, B.; Besserve, M.: Telling Cause from Effect in Deterministic Linear Dynamical Systems. In: International Conference on Machine Learning, 7-9 July 2015, Lille, France, pp. 285 - 294 (Eds. Bach , F.; Blei, D.). 32nd International Conference on Machine Learning (ICML 2015), Lille, France. International Machine Learning Society, Madison, WI, USA (2015)
18.
Conference Paper
Schölkopf, B.; Janzing, D.; Peters, J.; Sgouritsa, E.; Zhang, K.; Mooij, J.: On causal and anticausal learning. In: 29th International Conference on Machine Learning (ICML 2012), pp. 1255 - 1262 (Eds. Langford, J.; Pineau, J.). 29th International Conference on Machine Learning (ICML 2012), Edinburgh, UK. International Machine Learning Society, Madison, WI, USA (2012)
19.
Conference Paper
Mooij, J.; Janzing, D.; Heskes, T.; Schölkopf, B.: On Causal Discovery with Cyclic Additive Noise Models. In: Advances in Neural Information Processing Systems 24, pp. 639 - 647 (Eds. Shawe-Taylor, J.; Zemel, R.; Bartlett, P.; Pereira, F.; Weinberger, K.). Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS 2011), Granada, Spain. Curran, Red Hook, NY, USA (2012)
20.
Conference Paper
Besserve, M.; Janzing, D.; Logothetis, N.; Schölkopf, B.: Finding dependencies between frequencies with the kernel cross-spectral density. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), pp. 2080 - 2083. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), Praha, Czech Republic, May 22, 2011 - May 27, 2011. IEEE, Piscataway, NJ, USA (2011)
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