Jonas Martin Peters

Jonas Martin Peters

Professor

ORCID: 0000-0002-1487-7511

Publication year:
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  1. 2013

  2. Causal Inference on Time Series using Structural Equation Models

    Peters, Jonas Martin, Janzing, D. & Schölkopf, B., 2013, Advances in Neural Information Processing Systems 25 (NIPS). p. 585-592 8 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

  3. Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising

    Bottou, L., Peters, Jonas Martin, Quiñonero-Candela, J., Charles, D. X., Chickering, D. M., Portugualy, E., Ray, D., Simard, P. & Snelson, E., 2013, In: Journal of Machine Learning Research. 14, p. 3207-3260 54 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  4. Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders

    Sgouritsa, E., Janzing, D., Peters, Jonas Martin & Schölkopf, B., 2013, Proceedings of the 29th Annual Conference on Uncertainty in Artificial Intelligence (UAI). p. 556-565 10 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

  5. 2012

  6. On causal and anticausal learning

    Schölkopf, B., Janzing, D., Peters, Jonas Martin, Sgouritsa, E., Zhang, K. & Mooij, J. M., 2012, Proceedings of the 29th International Conference on Machine Learning (ICML). p. 1255-1262 8 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

  7. Published

    Restricted Structural Equation Models for Causal Inference

    Peters, Jonas Martin, 2012

    Research output: Book/Report › Report › Research

  8. 2011

  9. Causal Inference on Discrete Data Using Additive Noise Models

    Peters, Jonas Martin, Janzing, D. & Schölkopf, B., 2011, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 33, p. 2436-2450 15 p.

    Research output: Contribution to journal › Journal article › Research › peer-review

  10. Detecting low-complexity unobserved causes

    Janzing, D., Sgouritsa, E., Stegle, O., Peters, Jonas Martin & Schölkopf, B., 2011, Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI). p. 383-391 9 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

  11. Identifiability of Causal Graphs using Functional Models

    Peters, Jonas Martin, Mooij, J. M., Janzing, D. & Schölkopf, B., 2011, Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI). p. 589-598 10 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

  12. Kernel-based Conditional Independence Test and Application in Causal Discovery

    Zhang, K., Peters, Jonas Martin, Janzing, D. & Schölkopf, B., 2011, Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI). p. 804-813 10 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

  13. 2010

  14. Identifying Cause and Effect on Discrete Data using Additive Noise Models

    Peters, Jonas Martin, Janzing, D. & Schölkopf, B., 2010, AIStats 13. Journal of Machine Learning Research: Workshop and Conference Proceedings, Vol. 9. p. 597-604 8 p.

    Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review

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