{"type":"conference","year":"2017","language":[{"iso":"eng"}],"citation":{"ieee":"G. S. Martius and C. Lampert, “Extrapolation and learning equations,” in <i>5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings</i>, Toulon, France, 2017.","mla":"Martius, Georg S., and Christoph Lampert. “Extrapolation and Learning Equations.” <i>5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings</i>, International Conference on Learning Representations, 2017.","chicago":"Martius, Georg S, and Christoph Lampert. “Extrapolation and Learning Equations.” In <i>5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings</i>. International Conference on Learning Representations, 2017.","apa":"Martius, G. S., &#38; Lampert, C. (2017). Extrapolation and learning equations. In <i>5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings</i>. Toulon, France: International Conference on Learning Representations.","short":"G.S. Martius, C. Lampert, in:, 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings, International Conference on Learning Representations, 2017.","ama":"Martius GS, Lampert C. Extrapolation and learning equations. In: <i>5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings</i>. International Conference on Learning Representations; 2017.","ista":"Martius GS, Lampert C. 2017. Extrapolation and learning equations. 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings. ICLR: International Conference on Learning Representations."},"author":[{"first_name":"Georg S","full_name":"Martius, Georg S","last_name":"Martius","id":"3A276B68-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0001-8622-7887","first_name":"Christoph","full_name":"Lampert, Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","last_name":"Lampert"}],"conference":{"location":"Toulon, France","start_date":"2017-04-24","name":"ICLR: International Conference on Learning Representations","end_date":"2017-04-26"},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"6841","external_id":{"arxiv":["1610.02995"]},"date_updated":"2021-01-12T08:09:17Z","oa":1,"scopus_import":1,"publication_status":"published","day":"21","ec_funded":1,"department":[{"_id":"ChLa"}],"date_published":"2017-02-21T00:00:00Z","arxiv":1,"oa_version":"Preprint","abstract":[{"text":"In classical machine learning, regression is treated as a black box process of identifying a suitable function from a hypothesis set without attempting to gain insight into the mechanism connecting inputs and outputs. In the natural sciences, however, finding an interpretable function for a phenomenon is the prime goal as it allows to understand and generalize results. This paper proposes a novel type of function learning network, called equation learner (EQL), that can learn analytical expressions and is able to extrapolate to unseen domains. It is implemented as an end-to-end differentiable feed-forward network and allows for efficient gradient based training. Due to sparsity regularization concise interpretable expressions can be obtained. Often the true underlying source expression is identified.","lang":"eng"}],"project":[{"_id":"2532554C-B435-11E9-9278-68D0E5697425","name":"Lifelong Learning of Visual Scene Understanding","grant_number":"308036","call_identifier":"FP7"}],"main_file_link":[{"url":"https://arxiv.org/abs/1610.02995","open_access":"1"}],"title":"Extrapolation and learning equations","publisher":"International Conference on Learning Representations","date_created":"2019-09-01T22:01:00Z","month":"02","status":"public","quality_controlled":"1","publication":"5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings"}