---
_id: '6841'
abstract:
- lang: eng
  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.
arxiv: 1
author:
- first_name: Georg S
  full_name: Martius, Georg S
  id: 3A276B68-F248-11E8-B48F-1D18A9856A87
  last_name: Martius
- first_name: Christoph
  full_name: Lampert, Christoph
  id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
  last_name: Lampert
  orcid: 0000-0001-8622-7887
citation:
  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.'
  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.'
  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.
  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.
  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.'
  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.
  short: G.S. Martius, C. Lampert, in:, 5th International Conference on Learning Representations,
    ICLR 2017 - Workshop Track Proceedings, International Conference on Learning Representations,
    2017.
conference:
  end_date: 2017-04-26
  location: Toulon, France
  name: 'ICLR: International Conference on Learning Representations'
  start_date: 2017-04-24
date_created: 2019-09-01T22:01:00Z
date_published: 2017-02-21T00:00:00Z
date_updated: 2021-01-12T08:09:17Z
day: '21'
department:
- _id: ChLa
ec_funded: 1
external_id:
  arxiv:
  - '1610.02995'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/1610.02995
month: '02'
oa: 1
oa_version: Preprint
project:
- _id: 2532554C-B435-11E9-9278-68D0E5697425
  call_identifier: FP7
  grant_number: '308036'
  name: Lifelong Learning of Visual Scene Understanding
publication: 5th International Conference on Learning Representations, ICLR 2017 -
  Workshop Track Proceedings
publication_status: published
publisher: International Conference on Learning Representations
quality_controlled: '1'
scopus_import: 1
status: public
title: Extrapolation and learning equations
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
year: '2017'
...