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Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations.

R. Dangovski, L. Jing, C. Loh, S. Han, A. Srivastava, B. Cheung, P. Agrawal, and M. Soljacic. ICLR, OpenReview.net, (2022)

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Wilhelm Loh

Dietrich Loh

Kohua Loh

Ernesto Loh

Gunnar Loh

Other publications of authors with the same name

Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science.C. Loh, T. Christensen, R. Dangovski, S. Kim, and M. Soljacic. CoRR, (2021)Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure.S. Kim, P. Lu, C. Loh, J. Smith, J. Snoek, and M. Soljacic. Trans. Mach. Learn. Res., (2022)Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies.L. Han, S. Han, S. Sudalairaj, C. Loh, R. Dangovski, F. Deng, P. Agrawal, D. Metaxas, L. Karlinsky, T. Weng and 1 other author(s). CoRR, (2023)Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries.C. Loh, S. Han, S. Sudalairaj, R. Dangovski, K. Xu, F. Wenzel, M. Soljacic, and A. Srivastava. ICML, volume 202 of Proceedings of Machine Learning Research, page 22614-22630. PMLR, (2023)Equivariant Contrastive Learning.R. Dangovski, L. Jing, C. Loh, S. Han, A. Srivastava, B. Cheung, P. Agrawal, and M. Soljacic. CoRR, (2021)Multimodal Learning for Crystalline Materials.V. Moro, C. Loh, R. Dangovski, A. Ghorashi, A. Ma, Z. Chen, P. Lu, T. Christensen, and M. Soljacic. CoRR, (2023)Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems.S. Kim, P. Lu, C. Loh, J. Smith, J. Snoek, and M. Soljacic. CoRR, (2021)Automated lymph node detection and classification on breast and prostate cancer SPECT-CT images.L. Papp, N. Zsoter, C. Loh, B. Ole, B. Egeler, I. Garai, and U. Luetzen. EMBC, page 3431-3434. IEEE, (2011)On the Importance of Calibration in Semi-supervised Learning.C. Loh, R. Dangovski, S. Sudalairaj, S. Han, L. Han, L. Karlinsky, M. Soljacic, and A. Srivastava. CoRR, (2022)Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations.R. Dangovski, L. Jing, C. Loh, S. Han, A. Srivastava, B. Cheung, P. Agrawal, and M. Soljacic. ICLR, OpenReview.net, (2022)

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Disambiguation of "Loh, Charlotte"

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Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations.

Please choose a person to relate this publication to

Wilhelm Loh

Dietrich Loh

Kohua Loh

Ernesto Loh

Gunnar Loh

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Loh, Charlotte"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations.

Please choose a person to relate this publication to

Wilhelm Loh

Dietrich Loh

Kohua Loh

Ernesto Loh

Gunnar Loh

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
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APA
Chicago
DIN 1505
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Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations.