Contact

Jonas Peters

Adresse: Spemannstr. 38
72076 Tübingen

 

Bild von Peters, Jonas

Jonas Peters

Position: Group Leader  Abteilung: 

Scientific Interests
I am working on causal inference problems. Especially, I am interested in recovering the causal DAGs from iid data (continuous and discrete) and from single instances of time series.
In my diploma thesis I developed a method that tries to rediscover the correct time direction when given a real-world time series and its reversed sample.
If you like, have a look at our group homepage where you can find publications, data, code, etc..

Personal interests

Education

2009 - PhD Student at MPI for Biological Cybernetics in Tuebingen
2009 Diploma in Mathematics at University of Heidelberg
2007-2008 Diploma Thesis at MPI for Biological Cybernetics in Tuebingen
2006-2007 Master of Advanced Study (Part III, Mathematics) at University of Cambridge
2005 Pre-Diploma in Mathematics at University of Heidelberg
2002 Abitur at Burg-Gymnasium Bad Bentheim
2001 Participation in Pupil's Academy in Braunschweig

Professional Experience

2009-2010 Tutor at Pupil's Academy in Rostock
2005-2006 Scientific Employee at University of Heidelberg (Tutor and Professor's Assistant)
2002-2003 Civilian Service (Administration of a Children's Home)

Scholarships and Awards

2004-2008 Scholar of the German National Academic Foundation (Studienstiftung des Deutschen Volkes)
2007 UNWIN prize and election to scholar (Downing College, Cambridge)
2006-2007 Scholar of European Excellence Programme (EEP) of DAAD, Kurt-Hahn-Trust and Hoelderlin Programme (Allianz)

Personal Interests

Cello, Chess, Football, Climate Change, Biking, Hiking

Präferenzen: 
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Zeige Zusammenfassung

Artikel (1):

Peters J, Janzing D und Schölkopf B (Dezember-2011) Causal Inference on Discrete Data using Additive Noise Models IEEE Transactions on Pattern Analysis and Machine Intelligence 33(12) 2436-2450.
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Beiträge zu Tagungsbänden (10):

Schölkopf B, Janzing D, Peters J, Sgouritsa E, Zhang K und Mooij J (Juli-2012) On causal and anticausal learning, 29th International Conference on Machine Learning (ICML 2012), International Machine Learning Society, Madison, WI, USA, 1255-1262.
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Janzing D, Sgouritsa E, Stegle O, Peters J und Schölkopf B (Juli-2011) Detecting low-complexity unobserved causes, 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), AUAI Press, Corvallis, OR, USA, 383-391.
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Peters J, Mooij J, Janzing D und Schölkopf B (Juli-2011) Identifiability of causal graphs using functional models, 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), AUAI Press, Corvallis, OR, USA, 589-598.
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Zhang K, Peters J, Janzing D und Schölkopf B (Juli-2011) Kernel-based Conditional Independence Test and Application in Causal Discovery, 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), AUAI Press, Corvallis, OR, USA, 804-813.
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Peters J, Janzing D und Schölkopf B (Mai-2010) Identifying Cause and Effect on Discrete Data using Additive Noise Models, Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010), International Machine Learning Society, Madison, WI, USA, 597-604, Series: JMLR Workshop and Conference Proceedings ; 9.
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Peters J, Janzing D, Gretton A und Schölkopf B (2010) Kernel Methods for Detecting the Direction of Time Series In: Advances in Data Analysis, Data Handling and Business Intelligence, , 32nd Annual Conference of the Gesellschaft für Klassifikation e.V. (GfKl 2008), Springer, Berlin, Germany, 57-66, Series: Studies in Classification, Data Analysis, and Knowledge Organization.
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Peters J, Janzing D, Gretton A und Schölkopf B (Juni-2009) Detecting the Direction of Causal Time Series, 26th International Conference on Machine Learning (ICML 2009), ACM Press, New York, NY, USA, 801-808.
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Janzing D, Peters J, Mooij JM und Schölkopf B (Juni-2009) Identifying confounders using additive noise models, 25th Conference on Uncertainty in Artificial Intelligence (UAI 2009), AUAI Press, Corvallis, OR, USA, 249-257.
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Hoyer PO, Janzing D, Mooij JM, Peters J und Schölkopf B (Juni-2009) Nonlinear causal discovery with additive noise models In: Advances in neural information processing systems 21, , Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Curran, Red Hook, NY, USA, 689-696.
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Mooij JM, Janzing D, Peters J und Schölkopf B (Juni-2009) Regression by dependence minimization and its application to causal inference in additive noise models, 26th International Conference on Machine Learning (ICML 2009), ACM Press, New York, NY, USA, 745-752.
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Abschlussarbeiten (1):

Peters J: Asymmetries of Time Series under Inverting their Direction, University of Heidelberg, (August-2008). Diplom thesis
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Last updated: Montag, 22.05.2017