Raghavendra Selvan
Orcid: 0000-0003-4302-0207Affiliations:
- University of Copenhagen, Denmark
According to our database1,
Raghavendra Selvan
authored at least 41 papers
between 2016 and 2024.
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Bibliography
2024
A GPU-Accelerated Open-Source Python Package for Calculating Powder Diffraction, Small-Angle-, and Total Scattering with the Debye Scattering Equation.
J. Open Source Softw., April, 2024
CoRR, 2024
Adversarial Fine-tuning of Compressed Neural Networks for Joint Improvement of Robustness and Efficiency.
CoRR, 2024
CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Activation Compression of Graph Neural Networks Using Block-Wise Quantization with Improved Variance Minimization.
Proceedings of the IEEE International Conference on Acoustics, 2024
Proceedings of the IEEE International Conference on Acoustics, 2024
2023
CoRR, 2023
Explicit Temporal Embedding in Deep Generative Latent Models for Longitudinal Medical Image Synthesis.
CoRR, 2023
Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation.
Proceedings of the 2023 Northern Lights Deep Learning Workshop, 2023
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023
2022
CoRR, 2022
Identifying Partial Mouse Brain Microscopy Images from the Allen Reference Atlas Using a Contrastively Learned Semantic Space.
Proceedings of the Biomedical Image Registration - 10th International Workshop, 2022
Hybrid Ladder Transformers with Efficient Parallel-Cross Attention for Medical Image Segmentation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022
Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Interpreting Latent Spaces of Generative Models for Medical Images Using Unsupervised Methods.
Proceedings of the Deep Generative Models - Second MICCAI Workshop, 2022
2021
Dynamic <i>β</i>-VAEs for quantifying biodiversity by clustering optically recorded insect signals.
Ecol. Informatics, 2021
Detection of foraging behavior from accelerometer data using U-Net type convolutional networks.
Ecol. Informatics, 2021
Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networks.
CoRR, 2021
Dynamic β-VAEs for quantifying biodiversity by clustering optically recorded insect signals.
CoRR, 2021
Proceedings of the Information Processing in Medical Imaging, 2021
2020
Graph refinement based airway extraction using mean-field networks and graph neural networks.
Medical Image Anal., 2020
Locally orderless tensor networks for classifying two- and three-dimensional medical images.
CoRR, 2020
Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models.
CoRR, 2020
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020
2019
IEEE Trans. Medical Imaging, 2019
A Joint 3D UNet-Graph Neural Network-Based Method for Airway Segmentation from Chest CTs.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019
2018
Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks.
CoRR, 2018
Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses.
CoRR, 2018
Mean Field Network Based Graph Refinement with Application to Airway Tree Extraction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
2017
Proceedings of the Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 2017
2016
A Batch Algorithm for Estimating Trajectories of Point Targets Using Expectation Maximization.
IEEE Trans. Signal Process., 2016
CoRR, 2016