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Song J., Ermon S., 2019, arXiv preprint arXiv:1910.06222
Original
1910
Earlier work this paper cites.
Ruppert D., 1988, Technical report, Efficient estimations from a slowly convergent Robbins-Monro process. Cornell University Operations Research and Industrial Engineering
1988
Earlier work this paper cites.
Chen T., Kornblith S., Norouzi M., Hinton G., 2020, A Simple Framework for Contrastive Learning of Visual Representations ( arXiv:2002.05709 )
Original
2002
Earlier work this paper cites.
Buciluǎ C., Caruana R., Niculescu-Mizil A., 2006, in Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining. pp 535–541
2006
Earlier work this paper cites.
Dosovitskiy A., et al., 2020, arXiv preprint arXiv:2010.11929
Original
2010
Earlier work this paper cites.
Gutmann M., Hyvärinen A., 2010, in Teh Y. W., Titterington M., eds, Proceedings of Machine Learning Research Vol. 9, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. PMLR, Chia Laguna Resort, Sardinia, Italy, pp 297–304, https://proceedings.mlr.press/v9/gutmann10a.html
2010
Earlier work this paper cites.
Laureijs R., et al., 2011, arXiv preprint arXiv:1110.3193
Original
2011
Earlier work this paper cites.
Bahdanau D., Cho K., Bengio Y., 2014, arXiv preprint arXiv:1409.0473
Original
2014
Earlier work this paper cites.
Rezende D., Mohamed S., 2015, in International conference on machine learning. pp 1530–1538
2015
Earlier work this paper cites.
Dinh L., Sohl-Dickstein J., Bengio S., 2016, arXiv preprint arXiv:1605.08803
Original
2016
Earlier work this paper cites.
He K., Zhang X., Ren S., Sun J., 2016, in Proceedings of the IEEE conference on computer vision and pattern recognition. pp 770–778
2016
Earlier work this paper cites.
Papamakarios G., Murray I., 2016, Advances in neural information processing systems, 29
2016
Earlier work this paper cites.
Lueckmann J.-M., Goncalves P. J., Bassetto G., Öcal K., Nonnenmacher M., Macke J. H., 2017, Advances in neural information processing systems, 30
2017
Earlier work this paper cites.
Vaswani A., Shazeer N., Parmar N., Uszkoreit J., Jones L., Gomez A. N., Kaiser Ł., Polosukhin I., 2017, Advances in neural information processing systems, 30
2017
Earlier work this paper cites.
Caron M., Bojanowski P., Joulin A., Douze M., 2018, in Proceedings of the European conference on computer vision (ECCV). pp 132–149
2018
Earlier work this paper cites.
Devlin J., Chang M.-W., Lee K., Toutanova K., 2018, arXiv preprint arXiv:1810.04805
Original
2018
Earlier work this paper cites.
Sablayrolles A., Douze M., Schmid C., Jégou H., 2018, arXiv preprint arXiv:1806.03198
Original
2018
Earlier work this paper cites.
Serra J., Pascual S., Karatzoglou A., 2018, in CCIA. pp 120–129
2018
Earlier work this paper cites.

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2023

AstroCLIP: A Cross-Modal Foundation Model for Galaxies

Parker, Liam, Lanusse, Francois, Golkar, Siavash et al.

Understand

We present AstroCLIP, a single, versatile model that can embed both galaxy images and spectra into a shared, physically meaningful latent space.

These embeddings can then be used - without any model fine-tuning - for a variety of downstream tasks including (1) accurate in-modality and cross-modality semantic similarity search, (2) photometric redshift estimation, (3) galaxy property estimation from both images and spectra, and (4) morphology classification.
Our approach to implementing AstroCLIP consists of two parts.
First, we embed galaxy images and spectra separately by pretraining separate transformer-based image and spectrum encoders in self-supervised settings.

Built on

Song J., Ermon S., 2019, arXiv preprint arXiv:1910.06222
Original
1910
Earlier work this paper cites.
Ruppert D., 1988, Technical report, Efficient estimations from a slowly convergent Robbins-Monro process. Cornell University Operations Research and Industrial Engineering
1988
Earlier work this paper cites.
Chen T., Kornblith S., Norouzi M., Hinton G., 2020, A Simple Framework for Contrastive Learning of Visual Representations ( arXiv:2002.05709 )
Original
2002
Earlier work this paper cites.
Buciluǎ C., Caruana R., Niculescu-Mizil A., 2006, in Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining. pp 535–541
2006
Earlier work this paper cites.
Dosovitskiy A., et al., 2020, arXiv preprint arXiv:2010.11929
Original
2010
Earlier work this paper cites.
Gutmann M., Hyvärinen A., 2010, in Teh Y. W., Titterington M., eds, Proceedings of Machine Learning Research Vol. 9, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. PMLR, Chia Laguna Resort, Sardinia, Italy, pp 297–304, https://proceedings.mlr.press/v9/gutmann10a.html
2010
Earlier work this paper cites.
Laureijs R., et al., 2011, arXiv preprint arXiv:1110.3193
Original
2011
Earlier work this paper cites.
Bahdanau D., Cho K., Bengio Y., 2014, arXiv preprint arXiv:1409.0473
Original
2014
Earlier work this paper cites.
Rezende D., Mohamed S., 2015, in International conference on machine learning. pp 1530–1538
2015
Earlier work this paper cites.
Dinh L., Sohl-Dickstein J., Bengio S., 2016, arXiv preprint arXiv:1605.08803
Original
2016
Earlier work this paper cites.
He K., Zhang X., Ren S., Sun J., 2016, in Proceedings of the IEEE conference on computer vision and pattern recognition. pp 770–778
2016
Earlier work this paper cites.
Papamakarios G., Murray I., 2016, Advances in neural information processing systems, 29
2016
Earlier work this paper cites.
Lueckmann J.-M., Goncalves P. J., Bassetto G., Öcal K., Nonnenmacher M., Macke J. H., 2017, Advances in neural information processing systems, 30
2017
Earlier work this paper cites.
Vaswani A., Shazeer N., Parmar N., Uszkoreit J., Jones L., Gomez A. N., Kaiser Ł., Polosukhin I., 2017, Advances in neural information processing systems, 30
2017
Earlier work this paper cites.
Caron M., Bojanowski P., Joulin A., Douze M., 2018, in Proceedings of the European conference on computer vision (ECCV). pp 132–149
2018
Earlier work this paper cites.
Devlin J., Chang M.-W., Lee K., Toutanova K., 2018, arXiv preprint arXiv:1810.04805
Original
2018
Earlier work this paper cites.
Sablayrolles A., Douze M., Schmid C., Jégou H., 2018, arXiv preprint arXiv:1806.03198
Original
2018
Earlier work this paper cites.
Serra J., Pascual S., Karatzoglou A., 2018, in CCIA. pp 120–129
2018
Earlier work this paper cites.

Similar

van den Oord A., Li Y., Vinyals O., 2018, CoRR, abs/1807.03748
Original
2018
Cited alongside, same era.
Dey A., et al., 2019, arXiv preprint arXiv:1804.08657
Original
2019
Cited alongside, same era.
Durkan C., Bekasov A., Murray I., Papamakarios G., 2019, Advances in neural information processing systems, 32
2019
Cited alongside, same era.
Greenberg D., Nonnenmacher M., Macke J., 2019, in International Conference on Machine Learning. pp 2404–2414
2019
Cited alongside, same era.
Ivezić et. al. Ž., 2019, The Astrophysical Journal , 873, 111
2019
Cited alongside, same era.

Then

Hayat M. A., Harrington P. Z., Stein G., Luki’c Z., Mustafa M., 2021, ArXiv, abs/2101.04293
Original
2021
Later among the works it cites.
He K., Chen X., Xie S., Li Y., Dollár P., Girshick R., 2021, Masked Autoencoders Are Scalable Vision Learners ( arXiv:2111.06377 )
Original
2021
Later among the works it cites.
Radford A., et al., 2021, in International Conference on Machine Learning. https://api.semanticscholar.org/CorpusID:231591445
2021
Later among the works it cites.
Zhou J., Wei C., Wang H., Shen W., Xie C., Yuille A., Kong T., 2021, arXiv preprint arXiv:2111.07832
Original
2021
Later among the works it cites.
Teimoorinia H., Archinuk F., Woo J., Shishehchi S., Bluck A. F., 2022, The Astronomical Journal, 163, 71
2022

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Cited alongside, same era.

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Cited alongside, same era.

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Cited alongside, same era.

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Later among the works it cites.

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Later among the works it cites.

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