Raghavendra Selvan

Orcid: 0000-0003-4302-0207

Affiliations:
  • University of Copenhagen, Denmark


According to our database1, Raghavendra Selvan authored at least 41 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

On csauthors.net:

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

BMRS: Bayesian Model Reduction for Structured Pruning.
CoRR, 2024

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge.
CoRR, 2024

Equity through Access: A Case for Small-scale Deep Learning.
CoRR, 2024

Adversarial Fine-tuning of Compressed Neural Networks for Joint Improvement of Robustness and Efficiency.
CoRR, 2024

Is Adversarial Training with Compressed Datasets Effective?
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

EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search.
Proceedings of the IEEE International Conference on Acoustics, 2024

2023
Efficiency is Not Enough: A Critical Perspective of Environmentally Sustainable AI.
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

Operating Critical Machine Learning Models in Resource Constrained Regimes.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023

2022
Energy Consumption-Aware Tabular Benchmarks for Neural Architecture Search.
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

Patch-based medical image segmentation using Quantum Tensor Networks.
CoRR, 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

Segmenting Two-Dimensional Structures with Strided Tensor Networks.
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

Multi-layered tensor networks for image classification.
CoRR, 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

Lung Segmentation from Chest X-rays using Variational Data Imputation.
CoRR, 2020

Tensor Networks for Medical Image Classification.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Uncertainty Quantification in Medical Image Segmentation with Normalizing Flows.
Proceedings of the Machine Learning in Medical Imaging - 11th International Workshop, 2020

2019
Increasing Accuracy of Optimal Surfaces Using Min-Marginal Energies.
IEEE Trans. Medical Imaging, 2019

Segmentation of Roots in Soil with U-Net.
CoRR, 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

Extraction of Airways using Graph Neural Networks.
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
Extraction of Airways with Probabilistic State-Space Models and Bayesian Smoothing.
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

Extraction of airway trees using multiple hypothesis tracking and template matching.
CoRR, 2016


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