Scale out for large minibatch SGD: Residual network training on ImageNet-1K with improved accuracy and reduced time to train. - Valeriu Codreanu; Damian Podareanu; Vikram A. Saletore (CoRR, 2017)

Distributed Training of Generative Adversarial Networks for Fast Detector Simulation. - Sofia Vallecorsa; Federico Carminati; Gulrukh Khattak; Damian Podareanu; Valeriu Codreanu; Vikram A. Saletore; Hans Pabst (ISC Workshops, 2018)

Densifying Assumed-Sparse Tensors - Improving Memory Efficiency and MPI Collective Performance During Tensor Accumulation for Parallelized Training of Neural Machine Translation Models. - Derya Cavdar; Valeriu Codreanu; Can Karakus; John A. Lockman III; Damian Podareanu; Vikram A. Saletore; Alexander Sergeev; Don D. Smith II; Victor Suthichai; Quy Ta; Srinivas Varadharajan; Lucas A. Wilson; et al. (ISC, 2019)

DeepGalaxy: Deducing the Properties of Galaxy Mergers from Images Using Deep Neural Networks. - Maxwell X. Cai; Jeroen Bédorf; Vikram A. Saletore; Valeriu Codreanu; Damian Podareanu; Adel Chaibi; Penny X. Qian (DLS@SC, 2020)

Deep-learning enhancement of large scale numerical simulations. - Caspar van Leeuwen; Damian Podareanu; Valeriu Codreanu; Maxwell X. Cai; Axel Berg; Simon Portegies Zwart; Robin Stoffer; Menno Veerman; Chiel van Heerwaarden; Sydney Otten; Sascha Caron; Cunliang Geng; et al. (CoRR, 2020)

Predicting atmospheric optical properties for radiative transfer computations using neural networks. - Menno A. Veerman; Robert Pincus; Robin Stoffer; Caspar van Leeuwen; Damian Podareanu; Chiel C. van Heerwaarden (CoRR, 2020)

Beneath the SURFace: An MRI-like View into the Life of a 21st-Century Datacenter. - Alexandru Uta; Kristian Laursen; Alexandru Iosup; Paul Melis; Damian Podareanu; Valeriu Codreanu (login Usenix Mag., 2020)

Beneath the SURFace: An MRI-like View into the Life of a 21st Century Datacenter. - Kristian Laursen; Alexandru Uta; Alexandru Iosup; Paul Melis; Damian Podareanu; Valeriu Codreanu (Zenodo, 2020)

A Holistic Analysis of Datacenter Operations: Resource Usage, Energy, and Workload Characterization - Extended Technical Report. - Laurens Versluis; Mehmet Çetin; Caspar Greeven; Kristian Laursen; Damian Podareanu; Valeriu Codreanu; Alexandru Uta; Alexandru Iosup (CoRR, 2021)

Neural Symplectic Integrator with Hamiltonian Inductive Bias for the Gravitational $N$-body Problem. - Maxwell X. Cai; Simon Portegies Zwart; Damian Podareanu (CoRR, 2021)

Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images. - Niccolò Marini; Sebastian Otálora; Damian Podareanu; Mart van Rijthoven; Jeroen van der Laak; Francesco Ciompi; Henning Müller; Manfredo Atzori (Frontiers Comput. Sci., 2021)

SURF Machine Metric Dataset [2019-12-29, 2020-08-07]. - Kristian Laursen; Alexandru Uta; Alexandru Iosup; Paul Melis; Damian Podareanu; Valeriu Codreanu (Zenodo, 2021)

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations. - Niccolò Marini; Stefano Marchesin 001; Sebastian Otálora; Marek Wodzinski; Alessandro Caputo; Mart van Rijthoven; Witali Aswolinskiy; John-Melle Bokhorst; Damian Podareanu; Edyta Petters; Svetla Boytcheva; Genziana Buttafuoco; et al. (npj Digit. Medicine, 2022)

DIANNA: Deep Insight And Neural Network Analysis. - Elena Ranguelova; Christiaan Meijer; Leon C. Oostrum; Yang Liu 304; Patrick Bos; Giulia Crocioni; Matthieu Laneuville; Bryan Cardenas Guevara; Rena Bakhshi; Damian Podareanu (J. Open Source Softw., 2022)

Less is not more: We need rich datasets to explore. - Laurens Versluis; Mehmet Çetin; Caspar Greeven; Kristian Laursen; Damian Podareanu; Valeriu Codreanu; Alexandru Uta; Alexandru Iosup (Future Gener. Comput. Syst., 2023)

Generic and ML Workloads in an HPC Datacenter: Node Energy, Job Failures, and Node-Job Analysis. - Xiaoyu Chu; Daniel Hofstätter; Shashikant Ilager; Sacheendra Talluri; Duncan Kampert; Damian Podareanu; Dmitry Duplyakin; Ivona Brandic; Alexandru Iosup (ICPADS, 2024)

Automatic Labels are as Effective as Manual Labels in Biomedical Images Classification with Deep Learning. - Niccolò Marini; Stefano Marchesin 001; Lluis Borras Ferris; Simon Püttmann; Marek Wodzinski; Riccardo Fratti; Damian Podareanu; Alessandro Caputo; Svetla Boytcheva; Simona Vatrano; Filippo Fraggetta; Iris Nagtegaal; et al. (CoRR, 2024)

Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning. - Niccolò Marini; Stefano Marchesin 001; Marek Wodzinski; Alessandro Caputo; Damian Podareanu; Bryan Cardenas Guevara; Svetla Boytcheva; Simona Vatrano; Filippo Fraggetta; Francesco Ciompi; Gianmaria Silvello; Henning Müller; et al. (Medical Image Anal., 2024)

Improving the speed and quality of cancer segmentation using lower resolution pathology images. - Jieyi Li; Anwar Osseyran; Ruben Hekster; Stevan Rudinac; Valeriu Codreanu; Damian Podareanu (Multim. Tools Appl., 2024)

Generic and ML Workloads in an HPC Datacenter. - Xiaoyu Chu; Daniel Hofstätter; Shashikant Ilager; Sacheendra Talluri; Duncan Kampert; Damian Podareanu; Dmitry Duplyakin; Ivona Brandic; Alexandru Iosup (Zenodo, 2024)

Generic and ML Workloads in an HPC Datacenter. - Xiaoyu Chu; Daniel Hofstätter; Shashikant Ilager; Sacheendra Talluri; Duncan Kampert; Damian Podareanu; Dmitry Duplyakin; Ivona Brandic; Alexandru Iosup (Zenodo, 2024)

Generic and ML Workloads in an HPC Datacenter. - Xiaoyu Chu; Daniel Hofstätter; Shashikant Ilager; Sacheendra Talluri; Duncan Kampert; Damian Podareanu; Dmitry Duplyakin; Ivona Brandic; Alexandru Iosup (Zenodo, 2024)

BioAnalyst: A Foundation Model for Biodiversity. - Athanasios Trantas; Martino Mensio; Stylianos Stasinos; Sebastian Gribincea; Taimur Khan; Damian Podareanu; Aliene van der Veen (CoRR, 2025)