Error-Aware Conversion from ANN to SNN via Post-training Parameter Calibration.
Int. J. Comput. Vis., September, 2024
Self-supervised learning for medical image data with anatomy-oriented imaging planes.
Medical Image Anal., 2024
A Concept-based Interpretable Model for the Diagnosis of Choroid Neoplasias using Multimodal Data.
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CoRR, 2024
Spiking Token Mixer: An event-driven friendly Former structure for spiking neural networks.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Co-learning Semantic-Aware Unsupervised Segmentation for Pathological Image Registration.
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.
Proceedings of the International Conference on Machine Learning, 2023
Converting Artificial Neural Networks to Spiking Neural Networks via Parameter Calibration.
CoRR, 2022
When Sparsity Meets Dynamic Convolution.
CoRR, 2022
Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting.
Proceedings of the Tenth International Conference on Learning Representations, 2022
A Unified Framework for Generalized Low-Shot Medical Image Segmentation With Scarce Data.
IEEE Trans. Medical Imaging, 2021
Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations.
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NeuroImage, 2021
Multi-modal Attention Network for Stock Movements Prediction.
CoRR, 2021
Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021
BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction.
Proceedings of the 9th International Conference on Learning Representations, 2021
Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks.
Proceedings of the 9th International Conference on Learning Representations, 2021
MixMix: All You Need for Data-Free Compression Are Feature and Data Mixing.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Empirical study of correlations in the fitness landscapes of combinatorial optimization problems.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
Benchmarking Measures of Network Controllability on Canonical Graph Models.
J. Nonlinear Sci., 2020
Learning in School: Multi-teacher Knowledge Inversion for Data-Free Quantization.
CoRR, 2020
Robust Medical Image Segmentation from Non-expert Annotations with Tri-network.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
RE: Warnings and caveats in brain controllability.
NeuroImage, 2019
Interpretable Multimodality Embedding of Cerebral Cortex Using Attention Graph Network for Identifying Bipolar Disorder.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Optimal trajectories of brain state transitions.
NeuroImage, 2017
The energy landscape underpinning module dynamics in the human brain connectome.
NeuroImage, 2017
On Structural Controllability of Symmetric (Brain) Networks.
CoRR, 2017
Stimulation-Based Control of Dynamic Brain Networks.
PLoS Comput. Biol., 2016
Controllability of Brain Networks.
CoRR, 2014
Optical mapping of optically paced embryonic hearts.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013
Altering embryonic cardiac dynamics with optical pacing.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012