JuLib | Articles & more - {"Data-Intensive Science and Federated Computing"}

1

Contribution to a book
Contribution to a conference proceedings

Sub-Grid Scale Modelling at Scale with Deep Learning and up to 60 Billion Degrees of Freedom

Bode, Mathis
2020

“...Data-Intensive Science and Federated Computing...”
OpenAccess OpenAccess

2

Lecture

Parallel and Scalable Machine Learning

Riedel, Morris
2020

“...Data-Intensive Science and Federated Computing...”
OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess

3

Lecture

Introduction to Machine Learning and Deep Learning

Jitsev, Jenia
2020

“...Data-Intensive Science and Federated Computing...”

4

Conference Presentation

Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning

Pleines, Marco
2020

“...Data-Intensive Science and Federated Computing...”

5

Contribution to a conference proceedings

Super-Resolution of Large Volumes of Sentinel-2 Images with High Performance Distributed Deep Learning

Zhang, Run
2020

“...Data-Intensive Science and Federated Computing...”
OpenAccess

6

Contribution to a conference proceedings

Scaling Up a Multispectral Resnet-50 to 128 GPUs

Sedona, Rocco
2020

“...Data-Intensive Science and Federated Computing...”
OpenAccess

7

Contribution to a book
Contribution to a conference proceedings

Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning

Rüttgers, Mario
2020

12321

“...Data-Intensive Science and Federated Computing...”
OpenAccess OpenAccess

8

Conference Presentation

Scaling Up a Multispectral Resnet-50 to 128 GPUs

Sedona, Rocco
2020

“...Data-Intensive Science and Federated Computing...”
OpenAccess

9

Conference Presentation

Super-Resolution of Large Volumes of Sentinel-2 Images with High Performance Distributed Deep Learning

Zhang, Run
2020

“...Data-Intensive Science and Federated Computing...”
OpenAccess

10

Conference / Event

Workshop on Machine Learning on HPC Systems (MLHPC)

Durillo, Juan J.
2020

“...Data-Intensive Science and Federated Computing...”

11

Contribution to a book
Contribution to a conference proceedings

Developing Exascale Computing at JSC

Suarez, Estela
2020

“...Data-Intensive Science and Federated Computing...”
OpenAccess OpenAccess

12

Contribution to a book
Contribution to a conference proceedings

Obstacle Tower Without Human Demonstrations: How Far a Deep Feed-Forward Network Goes with Reinforcement Learning

Pleines, Marco
2020

“...Data-Intensive Science and Federated Computing...”
OpenAccess

13

Journal Article

Remote Sensing Big Data Classification with High Performance Distributed Deep Learning

Sedona, Rocco
2019

Remote sensing, 11 (2019) 24, S. 3056 -

“...Data-Intensive Science and Federated Computing...”
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14

Talk (non-conference)

Towards Large Scale Continual Learning on Modular High Performance Computers

Jitsev, Jenia
2019

“...Data-Intensive Science and Federated Computing...”

15

Lecture

Introduction to Machine Learning

Jitsev, Jenia
2019

“...Data-Intensive Science and Federated Computing...”

16

Talk (non-conference)

Towards Neural Architectures for Large Scale Continual Learning

Jitsev, Jenia
2019

“...Data-Intensive Science and Federated Computing...”

17

Talk (non-conference)

The Prospects for AI on Modular Architectures

Jitsev, Jenia
2019

“...Data-Intensive Science and Federated Computing...”

18

Lecture

Introduction to Deep Learning Models

Riedel, Morris
2019

“...Data-Intensive Science and Federated Computing...”
OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess

19

Lecture

Parallel and Scalable Machine Learning

Riedel, Morris
2019

“...Data-Intensive Science and Federated Computing...”
OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess OpenAccess

20

Preprint

Using Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows

Bode, Mathis
2019

“...Data-Intensive Science and Federated Computing...”
Get full text OpenAccess OpenAccess

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