Extraction of airway trees using multiple hypothesis tracking and template matching. - Raghavendra Selvan; Jens Petersen; Jesper Johannes Holst Pedersen; Marleen de Bruijne (CoRR, 2016)

A Batch Algorithm for Estimating Trajectories of Point Targets Using Expectation Maximization. - Abu Sajana Rahmathullah; Raghavendra Selvan; Lennart Svensson (IEEE Trans. Signal Process., 2016)

Extraction of Airways with Probabilistic State-Space Models and Bayesian Smoothing. - Raghavendra Selvan; Jens Petersen; Jesper Holst Pedersen; Marleen de Bruijne (GRAIL/MFCA/MICGen@MICCAI, 2017)

Mean Field Network Based Graph Refinement with Application to Airway Tree Extraction. - Raghavendra Selvan; Max Welling; Jesper Holst Pedersen; Jens Petersen; Marleen de Bruijne (MICCAI (2), 2018)

Extraction of Airways using Graph Neural Networks. - Raghavendra Selvan; Thomas N. Kipf; Max Welling; Jesper Holst Pedersen; Jens Petersen; Marleen de Bruijne (CoRR, 2018)

Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses. - Raghavendra Selvan; Jens Petersen; Jesper Holst Pedersen; Marleen de Bruijne (CoRR, 2018)

Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks. - Raghavendra Selvan; Thomas N. Kipf; Max Welling; Jesper Holst Pedersen; Jens Petersen; Marleen de Bruijne (CoRR, 2018)

A Joint 3D UNet-Graph Neural Network-Based Method for Airway Segmentation from Chest CTs. - Antonio Garcia-Uceda Juarez; Raghavendra Selvan; Zaigham Saghir; Marleen de Bruijne (MLMI@MICCAI, 2019)

Segmentation of Roots in Soil with U-Net. - Abraham George Smith; Jens Petersen; Raghavendra Selvan; Camilla Ruø Rasmussen (CoRR, 2019)

Increasing Accuracy of Optimal Surfaces Using Min-Marginal Energies. - Jens Petersen; Andrés M. Arias Lorza; Raghavendra Selvan; Daniel Bos; Aad van der Lugt; Jesper Johannes Holst Pedersen; Mads Nielsen; Marleen de Bruijne (IEEE Trans. Medical Imaging, 2019)

Uncertainty Quantification in Medical Image Segmentation with Normalizing Flows. - Raghavendra Selvan; Frederik Faye; Jon Middleton; Akshay Pai (MLMI@MICCAI, 2020)

Tensor Networks for Medical Image Classification. - Raghavendra Selvan; Erik B. Dam (MIDL, 2020)

Lung Segmentation from Chest X-rays using Variational Data Imputation. - Raghavendra Selvan; Erik B. Dam; Sofus Rischel; Kaining Sheng; Mads Nielsen; Akshay Pai (CoRR, 2020)

Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models. - Lasse F. Wolff Anthony; Benjamin Kanding; Raghavendra Selvan (CoRR, 2020)

Locally orderless tensor networks for classifying two- and three-dimensional medical images. - Raghavendra Selvan; Silas Nyboe Ørting; Erik B. Dam (CoRR, 2020)

Multi-layered tensor networks for image classification. - Raghavendra Selvan; Silas Nyboe Ørting; Erik B. Dam (CoRR, 2020)

Graph refinement based airway extraction using mean-field networks and graph neural networks. - Raghavendra Selvan; Thomas Kipf; Max Welling; Antonio Garcia-Uceda Juarez; Jesper Holst Pedersen; Jens Petersen; Marleen de Bruijne (Medical Image Anal., 2020)

Segmenting Two-Dimensional Structures with Strided Tensor Networks. - Raghavendra Selvan; Erik B. Dam; Jens Petersen (IPMI, 2021)

Dynamic β-VAEs for quantifying biodiversity by clustering optically recorded insect signals. - Klas Rydhmer; Raghavendra Selvan (CoRR, 2021)

Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networks. - Antonio Garcia-Uceda Juarez; Raghavendra Selvan; Zaigham Saghir; Harm A. W. M. Tiddens; Marleen de Bruijne (CoRR, 2021)

Patch-based medical image segmentation using Quantum Tensor Networks. - Raghavendra Selvan; Erik B. Dam; Søren Alexander Flensborg; Jens Petersen (CoRR, 2021)

Detection of foraging behavior from accelerometer data using U-Net type convolutional networks. - Manh Cuong Ngô; Raghavendra Selvan; Outi Tervo; Mads Peter Heide-Jørgensen; Susanne Ditlevsen (Ecol. Informatics, 2021)

Dynamic β-VAEs for quantifying biodiversity by clustering optically recorded insect signals. - Klas Rydhmer; Raghavendra Selvan (Ecol. Informatics, 2021)

Interpreting Latent Spaces of Generative Models for Medical Images Using Unsupervised Methods. - Julian Schön; Raghavendra Selvan; Jens Petersen (DGM4MICCAI@MICCAI, 2022)

Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis. - Raghavendra Selvan; Nikhil Bhagwat; Lasse F. Wolff Anthony; Benjamin Kanding; Erik B. Dam (MICCAI (5), 2022)

Hybrid Ladder Transformers with Efficient Parallel-Cross Attention for Medical Image Segmentation. - Haozhe Luo; Changdong Yu; Raghavendra Selvan (MIDL, 2022)

Identifying Partial Mouse Brain Microscopy Images from the Allen Reference Atlas Using a Contrastively Learned Semantic Space. - Justinas Antanavicius; Roberto Leiras; Raghavendra Selvan (WBIR, 2022)

Energy Consumption-Aware Tabular Benchmarks for Neural Architecture Search. - Pedram Bakhtiarifard; Christian Igel; Raghavendra Selvan (CoRR, 2022)

Operating Critical Machine Learning Models in Resource Constrained Regimes. - Raghavendra Selvan; Julian Schön; Erik B. Dam (MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI, 2023)

Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation. - Nicklas Boserup; Raghavendra Selvan (NLDL, 2023)

Explicit Temporal Embedding in Deep Generative Latent Models for Longitudinal Medical Image Synthesis. - Julian Schön; Raghavendra Selvan; Lotte Nygård; Ivan Richter Vogelius; Jens Petersen (CoRR, 2023)

EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search. - Pedram Bakhtiarifard; Christian Igel; Raghavendra Selvan (ICASSP, 2024)

Activation Compression of Graph Neural Networks Using Block-Wise Quantization with Improved Variance Minimization. - Sebastian Eliassen; Raghavendra Selvan (ICASSP, 2024)

CHILI: Chemically-Informed Large-scale Inorganic Nanomaterials Dataset for Advancing Graph Machine Learning. - Ulrik Friis-Jensen; Frederik L. Johansen; Andy S. Anker; Erik B. Dam; Kirsten M. Ø. Jensen; Raghavendra Selvan (KDD, 2024)

BMRS: Bayesian Model Reduction for Structured Pruning. - Dustin Wright 001; Christian Igel; Raghavendra Selvan (NeurIPS, 2024)

Adversarial Fine-tuning of Compressed Neural Networks for Joint Improvement of Robustness and Efficiency. - Hallgrimur Thorsteinsson; Valdemar J. Henriksen; Tong Chen; Raghavendra Selvan (CoRR, 2024)

Equity through Access: A Case for Small-scale Deep Learning. - Raghavendra Selvan; Bob Pepin; Christian Igel; Gabrielle Samuel; Erik B. Dam (CoRR, 2024)

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge. - Hongwei Bran Li; Fernando Navarro; Ivan Ezhov; Amirhossein Bayat; Dhritiman Das; Florian Kofler; Suprosanna Shit; Diana Waldmannstetter; Johannes C. Paetzold; Xiaobin Hu; Benedikt Wiestler; Lucas Zimmer; et al. (CoRR, 2024)

When Can Memorization Improve Fairness? - Bob Pepin; Christian Igel; Raghavendra Selvan (CoRR, 2024)

A GPU-Accelerated Open-Source Python Package for Calculating Powder Diffraction, Small-Angle-, and Total Scattering with the Debye Scattering Equation. - Frederik L. Johansen; Andy S. Anker; Ulrik Friis-Jensen; Erik B. Dam; Kirsten M. Ø. Jensen; Raghavendra Selvan (J. Open Source Softw., 2024)

How CO2STLY Is CHI? The Carbon Footprint of Generative AI in HCI Research and What We Should Do About It. - Nanna Inie; Jeanette Falk; Raghavendra Selvan (CHI, 2025)

PePR: Performance Per Resource Unit as a Metric to Promote Small-scale Deep Learning. - Raghavendra Selvan; Bob Pepin; Christian Igel; Gabrielle Samuel; Erik B. Dam (NLDL, 2025)

Is Adversarial Training with Compressed Datasets Effective? - Tong Chen; Raghavendra Selvan (SCIA (1), 2025)

Oscillations Make Neural Networks Robust to Quantization. - Jonathan Wenshøj; Bob Pepin; Raghavendra Selvan (CoRR, 2025)

deCIFer: Crystal Structure Prediction from Powder Diffraction Data using Autoregressive Language Models. - Frederik L. Johansen; Ulrik Friis-Jensen; Erik Bjørnager Dam; Kirsten M. Ø. Jensen; Rocío Mercado; Raghavendra Selvan (CoRR, 2025)

Climate And Resource Awareness is Imperative to Achieving Sustainable AI (and Preventing a Global AI Arms Race). - Pedram Bakhtiarifard; Pinar Tözün; Christian Igel; Raghavendra Selvan (CoRR, 2025)

The HCI GenAI CO2ST Calculator: A Tool for Calculating the Carbon Footprint of Generative AI Use in Human-Computer Interaction Research. - Nanna Inie; Jeanette Falk; Raghavendra Selvan (CoRR, 2025)

Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices. - Luis Cruz 002; João Paulo Fernandes; Maja H. Kirkeby; Silverio Martínez-Fernández; June Sallou; Hina Anwar; Enrique Barba Roque; Justus Bogner; Joel Castaño; Fernando Castor; Aadil Chasmawala; Simão Cunha; et al. (CoRR, 2025)

Efficiency Is Not Enough: A Critical Perspective on Environmentally Sustainable AI. - Dustin Wright 001; Christian Igel; Gabrielle Samuel; Raghavendra Selvan (Commun. ACM, 2025)

UniPhyNet: A Unified Network For Multimodal Physiological Raw Signal Classification. - Renxiang Qiu; Raghavendra Selvan (CoRR, 2025)