Ran Liu

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Understand and Improve Contrastive Learning Methods for Visual Representation: A Review

Ran Liu, 2021 .

Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers

Eva L. Dyer, Ran Liu, M. Dabagia, 2022, bioRxiv.

Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity

Ran Liu, 2021 .

MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction

Eva L. Dyer, Erik C. Johnson, Ran Liu, 2023, NeurIPS.

Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers

Eva L. Dyer, Ran Liu, M. Dabagia, 2022, bioRxiv.

Deep Learning Based Analysis of Histopathological Images of Breast Cancer

Chaoyang Zhang, Ran Liu, Juanying Xie, 2019, Front. Genet..

A Multi-Scale and Multi-Level Fusion Approach for Deep Learning-Based Liver Lesion Diagnosis in Magnetic Resonance Images with Visual Explanation

Ran Liu, Zheng Zhu, Yuchai Wan, 2021, Life.

Multi-Scale Modeling of Neural Structure in X-Ray Imagery

Eva L. Dyer, Aishwarya H. Balwani, Joseph D. Miano, 2021, 2021 IEEE International Conference on Image Processing (ICIP).

Robust Rank-Constrained Sparse Learning: A Graph-Based Framework for Single View and Multiview Clustering

Xuelong Li, Qi Wang, Ran Liu, 2021, IEEE Transactions on Cybernetics.

Robust Rank Constrained Sparse Learning: A Graph-Based Method for Clustering

Qi Wang, Xuelong Li, Ran Liu, 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity

Michal Valko, Eva L. Dyer, Mohammad Gheshlaghi Azar, 2021, bioRxiv.

Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction pdf

Michal Valko, Eva L. Dyer, William Gray-Roncal, 2021, ArXiv.

Persistent Path-Spectral (PPS) Based Machine Learning for Protein-Ligand Binding Affinity Prediction

Ran Liu, Jie Wu, Xiang Liu, 2023, J. Chem. Inf. Model..

A generative modeling approach for interpreting population-level variability in brain structure

Ran Liu, Eva L. Dyer, Cem Subakan, 2020, bioRxiv.

Understand and Improve Contrastive Learning Methods for Visual Representation: A Review pdf

Ran Liu, Ran Liu, 2021, ArXiv.

LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration

Eva L. Dyer, Z. Kira, Ran Liu, 2023, 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).

Deep Learning-Based COVID-19 Diagnosis and Trend Predictions

Ran Liu, Juanying Xie, Mingzhao Wang, 2020 .