Loh, Charlotte

8 publications

NeurIPS 2024 OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step Owen Dugan, Donato M. Jiménez-Benetó, Charlotte Loh, Zhuo Chen, Rumen Dangovski, Marin Soljačić

NeurIPS 2024 QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation Zhuo Chen, Rumen Dangovski, Charlotte Loh, Owen Dugan, Di Luo, Marin Soljačić

NeurIPS 2023 Analyzing Generalization of Neural Networks Through Loss Path Kernels Yilan Chen, Wei Huang, Hao Wang, Charlotte Loh, Akash Srivastava, Lam Nguyen, Lily Weng

TMLR 2023 Mitigating Confirmation Bias in Semi-Supervised Learning via Efficient Bayesian Model Averaging Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava

ICML 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

NeurIPS 2023 Towards Robust and Generalizable Representations of Extracellular Data Using Contrastive Learning Ankit Vishnubhotla, Charlotte Loh, Akash Srivastava, Liam Paninski, Cole Hurwitz

TMLR 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

ICLR 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