Shi Gu

According to our database, Shi Gu authored at least 28 papers between 2012 and 2024.

Collaborative distances:

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

2024

Self-Supervised Learning for Medical Image Data with Anatomy-Oriented Imaging Planes.

Tianwei Zhang, Dong Wei, Mengmeng Zhua, Shi Gu, Yefeng Zheng

CoRR, 2024

A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data.

Yifan Wu, Yang Liu, Yue Yang, Michael S. Yao, Wenli Yang, Xuehui Shi, Lihong Yang, Dongjun Li, Yueming Liu, James C. Gee, Xuan Yang, Wenbin Wei, Shi Gu

CoRR, 2024

2023

Co-learning Semantic-Aware Unsupervised Segmentation for Pathological Image Registration.

Yang Liu, Shi Gu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks.

Shikuang Deng, Hao Lin, Yuhang Li, Shi Gu

Proceedings of the International Conference on Machine Learning, 2023

2022

Converting Artificial Neural Networks to Spiking Neural Networks via Parameter Calibration.

Yuhang Li, Shikuang Deng, Xin Dong, Shi Gu

CoRR, 2022

When Sparsity Meets Dynamic Convolution.

Shwai He, Yuhang Li, Chenbo Jiang, Shi Gu

CoRR, 2022

Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting.

Shikuang Deng, Yuhang Li, Shanghang Zhang, Shi Gu

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

A Unified Framework for Generalized Low-Shot Medical Image Segmentation With Scarce Data.

Hengji Cui, Dong Wei, Kai Ma, Shi Gu, Yefeng Zheng

IEEE Trans. Medical Imaging, 2021

Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations.

Zhen Yang, Qawi K. Telesford, Alexandre R. Franco, Ryan Lim, Shi Gu, Ting Xu, Lei Ai, Francisco X. Castellanos, Chao-Gan Yan, Stanley J. Colcombe, Michael P. Milham

NeuroImage, 2021

Multi-modal Attention Network for Stock Movements Prediction.

Shwai He, Shi Gu

CoRR, 2021

Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks.

Yuhang Li, Yufei Guo, Shanghang Zhang, Shikuang Deng, Yongqing Hai, Shi Gu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration.

Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, Shi Gu

Proceedings of the 38th International Conference on Machine Learning, 2021

BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction.

Yuhang Li, Ruihao Gong, Xu Tan, Yang Yang, Peng Hu, Qi Zhang, Fengwei Yu, Wei Wang, Shi Gu

Proceedings of the 9th International Conference on Learning Representations, 2021

Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks.

Shikuang Deng, Shi Gu

Proceedings of the 9th International Conference on Learning Representations, 2021

MixMix: All You Need for Data-Free Compression Are Feature and Data Mixing.

Yuhang Li, Feng Zhu, Ruihao Gong, Mingzhu Shen, Xin Dong, Fengwei Yu, Shaoqing Lu, Shi Gu

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Empirical study of correlations in the fitness landscapes of combinatorial optimization problems.

Longfei Zhang, Ke Li, Shi Gu

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020

Benchmarking Measures of Network Controllability on Canonical Graph Models.

Elena Wu-Yan, Richard F. Betzel, Evelyn Tang, Shi Gu, Fabio Pasqualetti, Danielle S. Bassett

J. Nonlinear Sci., 2020

Learning in School: Multi-teacher Knowledge Inversion for Data-Free Quantization.

Yuhang Li, Feng Zhu, Ruihao Gong, Mingzhu Shen, Fengwei Yu, Shaoqing Lu, Shi Gu

CoRR, 2020

Robust Medical Image Segmentation from Non-expert Annotations with Tri-network.

Tianwei Zhang, Lequan Yu, Na Hu, Su Lv, Shi Gu

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

2019

RE: Warnings and caveats in brain controllability.

Fabio Pasqualetti, Shi Gu, Danielle S. Bassett

NeuroImage, 2019

Interpretable Multimodality Embedding of Cerebral Cortex Using Attention Graph Network for Identifying Bipolar Disorder.

Huzheng Yang, Xiaoxiao Li, Yifan Wu, Siyi Li, Su Lu, James S. Duncan, James C. Gee, Shi Gu

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

2017

Optimal trajectories of brain state transitions.

Shi Gu, Richard F. Betzel, Marcelo Gomes Mattar, Matthew Cieslak, Philip R. Delio, Scott T. Grafton, Fabio Pasqualetti, Danielle S. Bassett

NeuroImage, 2017

The energy landscape underpinning module dynamics in the human brain connectome.

Arian Ashourvan, Shi Gu, Marcelo Gomes Mattar, Jean M. Vettel, Danielle S. Bassett

NeuroImage, 2017

On Structural Controllability of Symmetric (Brain) Networks.

Tommaso Menara, Shi Gu, Danielle S. Bassett, Fabio Pasqualetti

CoRR, 2017

2016

Stimulation-Based Control of Dynamic Brain Networks.

Sarah Feldt Muldoon, Fabio Pasqualetti, Shi Gu, Matthew Cieslak, Scott T. Grafton, Jean M. Vettel, Danielle S. Bassett

PLoS Comput. Biol., 2016

2014

Controllability of Brain Networks.

Shi Gu, Fabio Pasqualetti, Matthew Cieslak, Scott T. Grafton, Danielle S. Bassett

CoRR, 2014

2013

Optical mapping of optically paced embryonic hearts.

Yves T. Wang, Shi Gu, Andrew M. Rollins, Michael W. Jenkins

Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

2012

Altering embryonic cardiac dynamics with optical pacing.

Lindsy M. Peterson, Matt McPheeters, Lee Barwick, Shi Gu, Andrew M. Rollins, Michael W. Jenkins

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012