Jenia Jitsev
Jenia Jitsev
Lead Scalable Learning & Multi-Purpose AI (SLAMPAI) Lab, Juelich Supercomputing Center (JSC), ELLIS
Verified email at - Homepage
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Laion-5b: An open large-scale dataset for training next generation image-text models
C Schuhmann, R Beaumont, R Vencu, C Gordon, R Wightman, M Cherti, ...
Advances in Neural Information Processing Systems 35, 25278-25294, 2022
Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
C Schuhmann, R Vencu, R Beaumont, R Kaczmarczyk, C Mullis, A Katta, ...
arXiv preprint arXiv:2111.02114, 2021
Reproducible scaling laws for contrastive language-image learning
M Cherti, R Beaumont, R Wightman, M Wortsman, G Ilharco, C Gordon, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
Openflamingo: An open-source framework for training large autoregressive vision-language models
A Awadalla, I Gao, J Gardner, J Hessel, Y Hanafy, W Zhu, K Marathe, ...
arXiv preprint arXiv:2308.01390, 2023
Datacomp: In search of the next generation of multimodal datasets
SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis, T Nguyen, R Marten, ...
Advances in Neural Information Processing Systems 36, 2024
Using physics-informed enhanced super-resolution generative adversarial networks for subfilter modeling in turbulent reactive flows
M Bode, M Gauding, Z Lian, D Denker, M Davidovic, K Kleinheinz, J Jitsev, ...
Proceedings of the Combustion Institute 38 (2), 2617-2625, 2021
Hierarchical information-based clustering for connectivity-based cortex parcellation
NS Gorbach, C Schütte, C Melzer, M Goldau, O Sujazow, J Jitsev, ...
Frontiers in neuroinformatics 5, 18, 2011
Remote sensing big data classification with high performance distributed deep learning
R Sedona, G Cavallaro, J Jitsev, A Strube, M Riedel, JA Benediktsson
Remote Sensing 11 (24), 3056, 2019
Effect of pre-training scale on intra-and inter-domain, full and few-shot transfer learning for natural and X-Ray chest images
M Cherti, J Jitsev
2022 International Joint Conference on Neural Networks (IJCNN), 1-9, 2022
Adversarial domain adaptation to reduce sample bias of a high energy physics event classifier
JM Clavijo, P Glaysher, J Jitsev, JM Katzy
Machine learning: science and technology 3 (1), 015014, 2021
Deep learning for the automation of particle analysis in catalyst layers for polymer electrolyte fuel cells
A Colliard-Granero, M Batool, J Jankovic, J Jitsev, MH Eikerling, K Malek, ...
Nanoscale 14 (1), 10-18, 2022
Experience-driven formation of parts-based representations in a model of layered visual memory
J Jitsev, C V Der Malsburg
Frontiers in computational neuroscience 3, 636, 2009
Juwels booster–a supercomputer for large-scale ai research
S Kesselheim, A Herten, K Krajsek, J Ebert, J Jitsev, M Cherti, M Langguth, ...
High Performance Computing: ISC High Performance Digital 2021 International …, 2021
Corticostriatal circuit mechanisms of value-based action selection: Implementation of reinforcement learning algorithms and beyond
K Morita, J Jitsev, A Morrison
Behavioural brain research 311, 110-121, 2016
Super-resolution of large volumes of sentinel-2 images with high performance distributed deep learning
R Zhang, G Cavallaro, J Jitsev
IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020
Towards prediction of turbulent flows at high reynolds numbers using high performance computing data and deep learning
M Bode, M Gauding, JH Göbbert, B Liao, J Jitsev, H Pitsch
International Conference on High Performance Computing, 614-623, 2018
Learning from positive and negative rewards in a spiking neural network model of basal ganglia
J Jitsev, A Morrison, M Tittgemeyer
The 2012 International Joint Conference on Neural Networks (IJCNN), 1-8, 2012
Convolutional neural networks for high throughput screening of catalyst layer inks for polymer electrolyte fuel cells
MJ Eslamibidgoli, FP Tipp, J Jitsev, J Jankovic, MH Eikerling, K Malek
RSC advances 11 (51), 32126-32134, 2021
Prediction of acoustic fields using a lattice-Boltzmann method and deep learning
M Rüttgers, SR Koh, J Jitsev, W Schröder, A Lintermann
International Conference on High Performance Computing, 81-101, 2020
Off-line memory reprocessing following on-line unsupervised learning strongly improves recognition performance in a hierarchical visual memory
J Jitsev, C von der Malsburg
The 2010 International Joint Conference on Neural Networks (IJCNN), 1-8, 2010
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