- Versions < 0.1.0 have "no license", see https://choosealicense.com/no-permission/.
- Versions 0.1.0 to 0.3.1 are covered under the Non-Commercial License Agreement appended below.
- Versions 0.4.0 - present are covered under the Apache-2.0 license appended below.
Please note EPFL has filed a patent titled "Dimensionality reduction of time-series data, and systems and devices that use the resultant embeddings" (https://patents.google.com/patent/WO2023143843A1) so if this does not work for your non-academic use case, please contact the TTO Office at EPFL.
Copyright (2023-present) Mackenzie W. Mathis & Steffen Schneider
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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"Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below).
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"Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution."
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You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License.
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Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
Non-Commercial License Agreement: CEBRA
© All rights reserved. ECOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE, Switzerland, Laboratory of Prof. Mackenzie W. Mathis (UPMWMATHIS) and original authors: Steffen Schneider, Jin H Lee, Mackenzie W Mathis. 2023.
Introduction
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This license agreement sets forth the terms and conditions under which ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE ( EPFL), CH-1015 Lausanne, Switzerland and Prof. Mackenzie W. Mathis and code authors (hereafter "LICENSOR") will grant you (hereafter "LICENSEE") a fully-paid, non-exclusive, and non-transferable license for academic, non-commercial purposes only (hereafter “LICENSE”) to use the "CEBRA" computer software program (hereafter "PROGRAM").
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LICENSEE acknowledges that the PROGRAM is a research tool that is being supplied "as is", without any related services, improvements or warranties from LICENSOR and that this license is entered into in order to enable others to utilize the PROGRAM in their academic activities.
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The ideas covered in this work is also patent pending (as of Jan 2023): US 63/302,670 “DIMENSIONALITY REDUCTION OF TIME-SERIES DATA, AND SYSTEMS AND DEVICES THAT USE THE RESULTANT EMBEDDINGS”
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If this license is not appropriate for your application, please contact Prof. Mackenzie W. Mathis (mackenzie@post.harvard.edu) and/or the TTO office at EPFL (tto@epfl.ch) for a commercial use license.
Terms and Conditions of the LICENSE
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LICENSOR grants to LICENSEE a fully-paid up, non-exclusive, and non-transferable license to use the PROGRAM for academic, non-commercial purposes, upon the terms and conditions hereinafter set out and until termination of this license as set forth below.
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LICENSEE acknowledges the PROGRAM is provided "as is", without any related services or improvements from LICENSOR and that the LICENSE is entered into in order to enable others to utilize the PROGRAM in their academic activities.
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LICENSOR MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY REPRESENTATIONS OR WARRANTIES OF MERCHANTABILITY OR FITNESS FOR PARTICULAR PURPOSE OR THAT THE USE OF THE PROGRAM WILL NOT INFRINGE ANY PATENTS, COPYRIGHTS, TRADEMARKS OR OTHER RIGHTS. LICENSOR shall not be liable for any direct, indirect or consequential damages with respect to any claim by LICENSEE or any third party arising from this Agreement or use of the PROGRAM.
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LICENSEE agrees that it will use the PROGRAM, and any modifications, improvements, or derivatives to PROGRAM that LICENSEE may create (collectively, "IMPROVEMENTS") solely for academic, non-commercial purposes and shall not distribute or transfer the PROGRAM or any IMPROVEMENTS to any person without prior written permission from LICENSOR. Any IMPROVEMENTS must remain open source with a copy of this license. The terms "academic, non-commercial", as used in this Agreement, mean academic or other scholarly research which (a) is not undertaken for profit, or (b) is not intended to produce works, services, or data for commercial use, or (c) is neither conducted, nor funded, by a person or an entity engaged in the commercial use, application or exploitation of works similar to the PROGRAM.
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LICENSEE agrees that they shall credit the use of CEBRA with an appropriate citation: Steffen Schneider, Jin H. Lee, Mackenzie Weygandt Mathis. Learnable latent embeddings for joint behavioral and neural analysis. Nature 2023 doi: https://doi.org/10.1038/s41586-023-06031-6.
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Ownership of all rights, including copyright in the PROGRAM and in any material associated therewith, shall at all times remain with LICENSOR and LICENSEE agrees to preserve the same. LICENSEE agrees not to use any portion of the PROGRAM or of any IMPROVEMENTS in any machine-readable form outside the PROGRAM, nor to make any copies except for its internal use, without prior written consent of LICENSOR. LICENSEE agrees to maintain this license file with the source code and place the following copyright notice on any such copies:
© All rights reserved. ECOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE, Switzerland, Laboratory of Prof. Mackenzie W. Mathis (UPMWMATHIS) and original authors: Steffen Schneider, Jin H Lee, Mackenzie W Mathis. 2023.
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The LICENSE shall not be construed to confer any rights upon LICENSEE by implication or otherwise except as specifically set forth herein.
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This Agreement shall be governed by the material laws of Switzerland and any dispute arising out of this Agreement or use of the PROGRAM shall be brought before the courts of Lausanne, Switzerland.
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This Agreement and the LICENSE shall remain effective until expiration of the copyrights of the PROGRAM except that, upon any breach of this Agreement by LICENSEE, LICENSOR shall have the right to terminate the LICENSE immediately upon notice to LICENSEE.