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Book Chapter (26)

141.
Book Chapter
Smola, A.; Elisseeff, A.; Schölkopf, B.; Williamson, R.: Entropy numbers for convex combinations and MLPs. In: Advances in Large Margin Classifiers, pp. 369 - 387 (Eds. Smola, A.; Bartlett, P.; Schölkopf, B.; Schuurmans, D.). MIT Press, Cambridge, MA, USA (2000)
142.
Book Chapter
Schölkopf, B.: Support-Vektor-Lernen. In: Ausgezeichnete Informatikdissertationen 1997, pp. 135 - 150 (Eds. Hotz, G.; Fiedler, H.; Gorny, P.; Grass, W.; Hölldobler, S. et al.). Teubner, Stuttgart, Germany (1998)
143.
Book Chapter
Schölkopf, B.: Künstliches Lernen. In: Komplexe adaptive Systeme, pp. 93 - 117 (Eds. Bornholdt, S.; Feindt, P.). Röll, Dettelbach, Germany (1996)

Proceedings (9)

144.
Proceedings
Causality: Objectives and Assessment. NIPS 2008 Workshop: Causality: Objectives and Assessment , Whistler, BC, Canada, December 12, 2008. (2010)
145.
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)
146.
Proceedings
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, December 04, 2007 - December 07, 2007. (2007), 1690 pp.
147.
Proceedings
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, December 05, 2005 - December 08, 2005. MIT Press, Cambridge, MA, USA (2006), 1676 pp.
148.
Proceedings
Pattern Recognition: 26th DAGM Symposium: Tübingen, Germany, August 30 - September 1, 2004 (Lecture Notes in Computer Science, 3175). 26th Pattern Recognition Symposium, Tübingen, Germany, August 30, 2004 - September 01, 2004. Springer, Berlin, Germany (2004), 581 pp.
149.
Proceedings
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, December 08, 2003 - December 13, 2003. MIT Press, Cambridge, MA, USA (2004), 1621 pp.
150.
Proceedings
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, August 24, 2003 - August 27, 2003. Springer, Berlin, Germany (2003), 746 pp.
151.
Proceedings
Inference Principles and Model Selection (Dagstuhl Reports, 01301). Inference Principles and Model Selection: Dagstuhl Seminar 01301, Dagstuhl, Germany, July 23, 2001 - July 27, 2001. Leibniz-Zentrum für Informatik, Dagstul, Germany (2001)
152.
Proceedings
Advances in Kernel Methods: Support Vector Learning. Eleventh Annual Conference on Neural Information Processing (NIPS 1997), Breckenridge, CO, USA, December 01, 1997 - December 06, 1997. MIT Press, Cambridge, MA, USA (1999), 376 pp.

Conference Paper (214)

153.
Conference Paper
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, February 02, 2021 - February 09, 2021. (accepted)
154.
Conference Paper
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, pp. 15661 - 15672 (Eds. 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, December 09, 2019 - December 13, 2019. Curran, Red Hook, NY, USA (2020)
155.
Conference Paper
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, April 26, 2020 - April 30, 2020. (2020)
156.
Conference Paper
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, pp. 286 - 295. 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel, July 22, 2019 - July 25, 2019. Curran, Red Hook, NY, USA (2019)
157.
Conference Paper
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), Vol. 115, 53, pp. 296 - 313. 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel, July 22, 2019 - July 25, 2019. (2019)
158.
Conference Paper
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, July 14, 2018 - July 15, 2018. (2018)
159.
Conference Paper
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), pp. 1 - 3. International Conference on Medical Imaging with Deep Learning (MIDL 2018), Amsterdam, The Netherlands, July 04, 2018 - July 06, 2018. (2018)
160.
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)
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