Suchergebnisse

Buchkapitel (26)

141.
Buchkapitel
Schölkopf, B.: Support-Vektor-Lernen. In: Ausgezeichnete Informatikdissertationen 1997, S. 135 - 150 (Hg. Hotz, G.; Fiedler, H.; Gorny, P.; Grass, W.; Hölldobler, S. et al.). Teubner, Stuttgart, Germany (1998)
142.
Buchkapitel
Schölkopf, B.: Künstliches Lernen. In: Komplexe adaptive Systeme, S. 93 - 117 (Hg. Bornholdt, S.; Feindt, P.). Röll, Dettelbach, Germany (1996)

Konferenzband (9)

143.
Konferenzband
Causality: Objectives and Assessment. NIPS 2008 Workshop: Causality: Objectives and Assessment , Whistler, BC, Canada, 12. Dezember 2008. (2010)
144.
Konferenzband
Machine learning approaches to statistical dependences and causality (Dagstuhl Reports, 09401). Dagstuhl Seminar: Machine learning approaches to statistical dependences and causality , Schloss Dagstuhl, Germany, 27. September 2009 - 02. Oktober 2009. (2009)
145.
Konferenzband
Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference. Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), Vancouver, BC, Canada, 04. Dezember 2007 - 07. Dezember 2007. (2007), 1690 S.
146.
Konferenzband
Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference. Nineteenth Annual Conference on Neural Information Processing Systems (NIPS 2005), Vancouver, BC, Canada, 05. Dezember 2005 - 08. Dezember 2005. MIT Press, Cambridge, MA, USA (2006), 1676 S.
147.
Konferenzband
Pattern Recognition: 26th DAGM Symposium: Tübingen, Germany, August 30 - September 1, 2004 (Lecture Notes in Computer Science, 3175). 26th Pattern Recognition Symposium, Tübingen, Germany, 30. August 2004 - 01. September 2004. Springer, Berlin, Germany (2004), 581 S.
148.
Konferenzband
Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference. Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, 08. Dezember 2003 - 13. Dezember 2003. MIT Press, Cambridge, MA, USA (2004), 1621 S.
149.
Konferenzband
Learning theory and Kernel machines: 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003) (Lecture Notes in Computer Science, 2777). 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), Washington, DC, USA, 24. August 2003 - 27. August 2003. Springer, Berlin, Germany (2003), 746 S.
150.
Konferenzband
Inference Principles and Model Selection (Dagstuhl Reports, 01301). Inference Principles and Model Selection: Dagstuhl Seminar 01301, Dagstuhl, Germany, 23. Juli 2001 - 27. Juli 2001. Leibniz-Zentrum für Informatik, Dagstul, Germany (2001)
151.
Konferenzband
Advances in Kernel Methods: Support Vector Learning. Eleventh Annual Conference on Neural Information Processing (NIPS 1997), Breckenridge, CO, USA, 01. Dezember 1997 - 06. Dezember 1997. MIT Press, Cambridge, MA, USA (1999), 376 S.

Konferenzbeitrag (214)

152.
Konferenzbeitrag
Besserve, M.; Sun, R.; Janzing, D.; Schölkopf, B.: A theory of independent mechanisms for extrapolation in generative models. In: 35th AAAI Conference on Artificial Intelligence: A Virtual Conference. 35th AAAI Conference on Artificial Intelligence: A Virtual Conference, 02. Februar 2021 - 09. Februar 2021. (angenommen)
153.
Konferenzbeitrag
Gondal, M.; Wuthrich, M.; Miladinovic, D.; Locatello, F.; Breidt, M.; Volchkov, V.; Akpo, J.; Bachem, O.; Schölkopf, B.; Bauer, S.: On the Transfer of Inductive Biasfrom Simulation to the Real World: a New Disentanglement Dataset. In: Advances in Neural Information Processing Systems 32, S. 15661 - 15672 (Hg. Wallach, H.; Larochelle, H.; Beygelzimer , A.; d'Alché-Buc, F.; Fox, E. et al.). Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 09. Dezember 2019 - 13. Dezember 2019. Curran, Red Hook, NY, USA (2020)
154.
Konferenzbeitrag
Besserve, M.; Mehrjou, A.; Sun, R.; Schölkopf, B.: Counterfactuals uncover the modular structure of deep generative models. In: Eighth International Conference on Learning Representations (ICLR 2020). Eighth International Conference on Learning Representations (ICLR 2020), Addis Ababa, Ethiopia, 26. April 2020 - 30. April 2020. (2020)
155.
Konferenzbeitrag
Geiger, P.; Besserve, M.; Winkelmann, J.; Proissl, C.; Schölkopf, B.: Coordinating Users of Shared Facilities via Data-driven Predictive Assistants and Game Theory. In: 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), 49, S. 286 - 295. 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel, 22. Juli 2019 - 25. Juli 2019. Curran, Red Hook, NY, USA (2019)
156.
Konferenzbeitrag
Gresele, L.; Rubenstein, P.; Mehrjou, A.; Locatello, F.; Schölkopf, B.: The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA. In: 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Bd. 115, 53, S. 296 - 313. 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel, 22. Juli 2019 - 25. Juli 2019. (2019)
157.
Konferenzbeitrag
Besserve, M.; Sun, R.; Schölkopf, B.: Intrinsic disentanglement: an invariance view for deep generative models. In: ICML 2018 Workshop on Theoretical Foundations and Applications of Deep Generative Models. ICML 2018 Workshop on Theoretical Foundations and Applications of Deep Generative Models, Stockholm, Sweden, 14. Juli 2018 - 15. Juli 2018. (2018)
158.
Konferenzbeitrag
Loktyushin, A.; Ehses, P.; Schölkopf, B.; Scheffler, K.: Learning-based solution to phase error correction in T2*-weighted GRE scans. In: International Conference on Medical Imaging with Deep Learning (MIDL 2018), S. 1 - 3. International Conference on Medical Imaging with Deep Learning (MIDL 2018), Amsterdam, The Netherlands, 04. Juli 2018 - 06. Juli 2018. (2018)
159.
Konferenzbeitrag
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, S. 557 - 565 (Hg. Storkey , A.; Perez-Cruz, F.). 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018), Playa Blanca, Spain, 09. April 2018 - 11. April 2018. International Machine Learning Society, Madison, WI, USA (2018)
160.
Konferenzbeitrag
Loktyushin, A.; Schuler, C.; Scheffler, K.; Schölkopf, B.: Retrospective Motion Correction of Magnitude-Input MR Images. In: Machine Learning Meets Medical Imaging, S. 3 - 12 (Hg. Bhatia , K.K.). First International Workshop on Machine Learning Meets Medical Imaging (MLMMI 2015), held in conjunction with ICML 2015, Lille, France. IEEE, Piscataway, NJ, USA (2016)
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