Lu Mi

According to our database, Lu Mi authored at least 24 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Active learning of neural population dynamics using two-photon holographic optogenetics.

Andrew Wagenmaker, Lu Mi, Marton Rozsa, Matthew S. Bull, Karel Svoboda, Kayvon Daie, Matthew D. Golub, Kevin G. Jamieson

CoRR, 2024

Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Conditional Interpretations.

Xinyue Xu, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li

CoRR, 2024

LatticeGen: Hiding Generated Text in a Lattice for Privacy-Aware Large Language Model Generation on Cloud.

Mengke Zhang, Tianxing He, Tianle Wang, Lu Mi, Niloofar Mireshghallah, Binyi Chen, Hao Wang, Yulia Tsvetkov

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations.

Xinyue Xu, Yi Qin, Lu Mi, Hao Wang, Xiaomeng Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Attention for Causal Relationship Discovery from Biological Neural Dynamics.

Ziyu Lu, Anika Tabassum, Shruti R. Kulkarni, Lu Mi, J. Nathan Kutz, Eric Shea-Brown, Seung-Hwan Lim

CoRR, 2023

LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud.

Mengke Zhang, Tianxing He, Tianle Wang, Lu Mi, Fatemehsadat Mireshghallah, Binyi Chen, Hao Wang, Yulia Tsvetkov

CoRR, 2023

The XPRESS Challenge: Xray Projectomic Reconstruction - Extracting Segmentation with Skeletons.

Tri Nguyen, Mukul Narwani, Mark Larson, Yicong Li, Shuhan Xie, Hanspeter Pfister, Donglai Wei, Nir Shavit, Lu Mi, Alexandra Pacureanu, Wei-Chung Lee, Aaron T. Kuan

CoRR, 2023

Learning Time-Invariant Representations for Individual Neurons from Population Dynamics.

Lu Mi, Trung Le, Tianxing He, Eli Shlizerman, Uygar Sümbül

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

X-Ray2EM: Uncertainty-Aware Cross-Modality Image Reconstruction from X-Ray to Electron Microscopy in Connectomics.

Yicong Li, Yaron Meirovitch, Aaron T. Kuan, Jasper S. Phelps, Alexandra Pacureanu, Wei-Chung Allen Lee, Nir Shavit, Lu Mi

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Learning to Correct Sloppy Annotations in Electron Microscopy Volumes.

Minghao Chen, Mukesh Bangalore Renuka, Lu Mi, Jeff Lichtman, Nir Shavit, Yaron Meirovitch

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Deep Learning Tools for Next-Generation Connectomics

Lu Mi

PhD thesis, 2022

im2nerf: Image to Neural Radiance Field in the Wild.

Lu Mi, Abhijit Kundu, David A. Ross, Frank Dellaert, Noah Snavely, Alireza Fathi

CoRR, 2022

Subgraph Frequency Distribution Estimation using Graph Neural Networks.

Zhongren Chen, Xinyue Xu, Shengyi Jiang, Hao Wang, Lu Mi

CoRR, 2022

Connectome-constrained Latent Variable Model of Whole-Brain Neural Activity.

Lu Mi, Richard Xu, Sridhama Prakhya, Albert Lin, Nir Shavit, Aravinthan D. T. Samuel, Srinivas C. Turaga

Proceedings of the Tenth International Conference on Learning Representations, 2022

Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate.

Lu Mi, Hao Wang, Yonglong Tian, Hao He, Nir Shavit

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Revisiting Latent-Space Interpolation via a Quantitative Evaluation Framework.

Lu Mi, Tianxing He, Core Francisco Park, Hao Wang, Yue Wang, Nir Shavit

CoRR, 2021

HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps.

Lu Mi, Hang Zhao, Charlie Nash, Xiaohan Jin, Jiyang Gao, Chen Sun, Cordelia Schmid, Nir Shavit, Yuning Chai, Dragomir Anguelov

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Inter-harmonics analysis and parameter estimation based on H2R6 window and constructing low-interference zone.

Yanchun Xu, Yufei Du, Zhenxing Li, Lei Xi, Lu Mi

IET Commun., 2020

Learning Guided Electron Microscopy with Active Acquisition.

Lu Mi, Hao Wang, Yaron Meirovitch, Richard Schalek, Srinivas C. Turaga, Jeff W. Lichtman, Aravinthan D. T. Samuel, Nir Shavit

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

2019

Training-Free Uncertainty Estimation for Neural Networks.

Lu Mi, Hao Wang, Yonglong Tian, Nir Shavit

CoRR, 2019

Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics.

Yaron Meirovitch, Lu Mi, Hayk Saribekyan, Alexander Matveev, David Rolnick, Nir Shavit

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

A Probe Towards Understanding GAN and VAE Models.

Lu Mi, Macheng Shen, Jingzhao Zhang

CoRR, 2018

Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics.

Yaron Meirovitch, Lu Mi, Hayk Saribekyan, Alexander Matveev, David Rolnick, Casimir Wierzynski, Nir Shavit

CoRR, 2018

2016

Study of a Microfluidic Chip Integrating Single Cell Trap and 3D Stable Rotation Manipulation.

Liang Huang, Long Tu, Xueyong Zeng, Lu Mi, Xuzhou Li, Wenhui Wang

Micromachines, 2016