Charlotte Loh

According to our database, Charlotte Loh authored at least 12 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2023

Multimodal Learning for Crystalline Materials.

Viggo Moro, Charlotte Loh, Rumen Dangovski, Ali Ghorashi, Andrew Ma, Zhuo Chen, Peter Y. Lu, Thomas Christensen, Marin Soljacic

CoRR, 2023

Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies.

Ligong Han, Seungwook Han, Shivchander Sudalairaj, Charlotte Loh, Rumen Dangovski, Fei Deng, Pulkit Agrawal, Dimitris N. Metaxas, Leonid Karlinsky, Tsui-Wei Weng, Akash Srivastava

CoRR, 2023

Towards robust and generalizable representations of extracellular data using contrastive learning.

Ankit Vishnubhotla, Charlotte Loh, Akash Srivastava, Liam Paninski, Cole L. Hurwitz

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Analyzing Generalization of Neural Networks through Loss Path Kernels.

Yilan Chen, Wei Huang, Hao Wang, Charlotte Loh, Akash Srivastava, Lam M. Nguyen, Lily Weng

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries.

Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava

Proceedings of the International Conference on Machine Learning, 2023

2022

Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure.

Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic

Trans. Mach. Learn. Res., 2022

On the Importance of Calibration in Semi-supervised Learning.

Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava

CoRR, 2022

Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations.

Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Equivariant Contrastive Learning.

Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic

CoRR, 2021

Surrogate- and invariance-boosted contrastive learning for data-scarce applications in science.

Charlotte Loh, Thomas Christensen, Rumen Dangovski, Samuel Kim, Marin Soljacic

CoRR, 2021

Scalable and Flexible Deep Bayesian Optimization with Auxiliary Information for Scientific Problems.

Samuel Kim, Peter Y. Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic

CoRR, 2021

2011

Automated lymph node detection and classification on breast and prostate cancer SPECT-CT images.

Laszlo Papp, Norbert Zsoter, Charlotte Loh, Baeumer Ole, Bernhard Egeler, Ildikó Garai, Ulf Luetzen

Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011