Study of a Microfluidic Chip Integrating Single Cell Trap and 3D Stable Rotation Manipulation. - Liang Huang 004; Long Tu; Xueyong Zeng; Lu Mi; Xuzhou Li; Wenhui Wang 001 (Micromachines, 2016)

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)

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; Nir Shavit (CVPR, 2019)

Training-Free Uncertainty Estimation for Neural Networks. - Lu Mi; Hao Wang 014; Yonglong Tian; Nir Shavit (CoRR, 2019)

Learning Guided Electron Microscopy with Active Acquisition. - Lu Mi; Hao Wang 014; Yaron Meirovitch; Richard Schalek; Srinivas C. Turaga; Jeff W. Lichtman; Aravinthan D. T. Samuel; Nir Shavit (MICCAI (5), 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)

HDMapGen: A Hierarchical Graph Generative Model of High Definition Maps. - Lu Mi; Hang Zhao; Charlie Nash; Xiaohan Jin; Jiyang Gao; Chen Sun 002; Cordelia Schmid; Nir Shavit; Yuning Chai; Dragomir Anguelov (CVPR, 2021)

Revisiting Latent-Space Interpolation via a Quantitative Evaluation Framework. - Lu Mi; Tianxing He; Core Francisco Park; Hao Wang 014; Yue Wang; Nir Shavit (CoRR, 2021)

Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate. - Lu Mi; Hao Wang 014; Yonglong Tian; Hao He 011; Nir Shavit (AAAI, 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 (ICLR, 2022)

Subgraph Frequency Distribution Estimation using Graph Neural Networks. - Zhongren Chen; Xinyue Xu; Shengyi Jiang; Hao Wang; Lu Mi (CoRR, 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)

Deep Learning Tools for Next-Generation Connectomics - Lu Mi (2022)

Learning to Correct Sloppy Annotations in Electron Microscopy Volumes. - Minghao Chen; Mukesh Bangalore Renuka; Lu Mi; Jeff Lichtman; Nir Shavit; Yaron Meirovitch (CVPR Workshops, 2023)

X-Ray2EM: Uncertainty-Aware Cross-Modality Image Reconstruction from X-Ray to Electron Microscopy in Connectomics. - Yicong Li 002; Yaron Meirovitch; Aaron T. Kuan; Jasper S. Phelps; Alexandra Pacureanu; Wei-Chung Allen Lee 001; Nir Shavit; Lu Mi (ISBI, 2023)

Learning Time-Invariant Representations for Individual Neurons from Population Dynamics. - Lu Mi; Trung Le 002; Tianxing He; Eli Shlizerman; Uygar Sümbül (NeurIPS, 2023)

The XPRESS Challenge: Xray Projectomic Reconstruction - Extracting Segmentation with Skeletons. - Tri Nguyen; Mukul Narwani; Mark Larson; Yicong Li 002; Shuhan Xie; Hanspeter Pfister; Donglai Wei 001; Nir Shavit; Lu Mi; Alexandra Pacureanu; Wei-Chung Lee 001; Aaron T. Kuan (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 003; Lu Mi; Fatemehsadat Mireshghallah; Binyi Chen; Hao Wang 014; Yulia Tsvetkov (CoRR, 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)

Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations. - Xinyue Xu; Yi Qin; Lu Mi; Hao Wang 014; Xiaomeng Li (ICLR, 2024)

LatticeGen: Hiding Generated Text in a Lattice for Privacy-Aware Large Language Model Generation on Cloud. - Mengke Zhang; Tianxing He; Tianle Wang 003; Lu Mi; Niloofar Mireshghallah; Binyi Chen; Hao Wang 014; Yulia Tsvetkov (NAACL-HLT (Findings), 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 (NeurIPS, 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)

NetFormer: An interpretable model for recovering dynamical connectivity in neuronal population dynamics. - Ziyu Lu; Wuwei Zhang; Trung Le 002; Hao Wang; Uygar Sümbül; Eric Todd Shea-Brown; Lu Mi (ICLR, 2025)

MCM: Multi-layer Concept Map for Efficient Concept Learning from Masked Images. - Yuwei Sun; Lu Mi; Ippei Fujisawa; Ryota Kanai (CoRR, 2025)

Concept-Based Unsupervised Domain Adaptation. - Xinyue Xu; Yueying Hu; Hui Tang; Yi Qin 004; Lu Mi; Hao Wang; Xiaomeng Li 001 (CoRR, 2025)

SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding. - Trung Le 002; Hao Fang; Jingyuan Li; Tung Nguyen; Lu Mi; Amy L. Orsborn; Uygar Sümbül; Eli Shlizerman (CoRR, 2025)