Damian Podareanu

Orcid: 0000-0002-4207-8725

According to our database1, Damian Podareanu authored at least 14 papers between 2017 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Improving the speed and quality of cancer segmentation using lower resolution pathology images.
Multim. Tools Appl., January, 2024

2023
Less is not more: We need rich datasets to explore.
Future Gener. Comput. Syst., May, 2023

2022
DIANNA: Deep Insight And Neural Network Analysis.
J. Open Source Softw., December, 2022

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations.
npj Digit. Medicine, 2022

2021
Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images.
Frontiers Comput. Sci., 2021

Neural Symplectic Integrator with Hamiltonian Inductive Bias for the Gravitational $N$-body Problem.
CoRR, 2021

A Holistic Analysis of Datacenter Operations: Resource Usage, Energy, and Workload Characterization - Extended Technical Report.
CoRR, 2021

2020
Beneath the SURFace: An MRI-like View into the Life of a 21st-Century Datacenter.
login Usenix Mag., 2020

Predicting atmospheric optical properties for radiative transfer computations using neural networks.
CoRR, 2020

Deep-learning enhancement of large scale numerical simulations.
CoRR, 2020

DeepGalaxy: Deducing the Properties of Galaxy Mergers from Images Using Deep Neural Networks.
Proceedings of the Fourth IEEE/ACM Workshop on Deep Learning on Supercomputers, 2020

2019
Densifying Assumed-Sparse Tensors - Improving Memory Efficiency and MPI Collective Performance During Tensor Accumulation for Parallelized Training of Neural Machine Translation Models.
Proceedings of the High Performance Computing - 34th International Conference, 2019

2018
Distributed Training of Generative Adversarial Networks for Fast Detector Simulation.
Proceedings of the High Performance Computing, 2018

2017
Scale out for large minibatch SGD: Residual network training on ImageNet-1K with improved accuracy and reduced time to train.
CoRR, 2017


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