Enhancing Visual Inspection Capability of Multi-Modal Large Language Models on Medical Time Series with Supportive Conformalized and Interpretable Small Specialized Models.
CoRR, January, 2025
Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning.
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Proceedings of the Thirteenth International Conference on Learning Representations, 2025
A Computation and Energy Efficient Hardware Architecture for SSL Acceleration.
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Proceedings of the 30th Asia and South Pacific Design Automation Conference, 2025
DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal.
IEEE J. Biomed. Health Informatics, September, 2024
Knowledge distillation under ideal joint classifier assumption.
Neural Networks, 2024
Improving GPU Multi-Tenancy Through Dynamic Multi-Instance GPU Reconfiguration.
CoRR, 2024
Deep Inverse Design for High-Level Synthesis.
CoRR, 2024
A transformer-based diffusion probabilistic model for heart rate and blood pressure forecasting in Intensive Care Unit.
Comput. Methods Programs Biomed., 2024
Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
MTS-LOF: Medical Time-Series Representation Learning via Occlusion-Invariant Features.
CoRR, 2023
Knowledge Distillation Under Ideal Joint Classifier Assumption.
CoRR, 2023
TDSTF: Transformer-based Diffusion probabilistic model for Sparse Time series Forecasting.
CoRR, 2023
Sequence-level Supervised Deep Neural Networks for Mitosis Event Detection in Time-Lapse Microscopy Images.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020
Weakly Supervised Deep Learning for Detecting and Counting Dead Cells in Microscopy Images.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019