building 20.30, room 0.014
Aretha Teckentrup, Thomas O'Leary-Roseberry
The program includes short courses on the following topics:
Neural Operators: Thomas O'Leary-Roseberry (University of Texas), confirmed.
Gaussian Processes: Aretha Teckentrup (University of Edinburgh), confirmed.
Link between Gaussian Processes and Neural Networks (incl. Neural Operators): Tobias Weber (U Tübingen), confirmed.
Further, you can expect:
poster session and networking dinner on the first day
social event in the evening on the second day
sessions that combine mathematical theory with application and real-life examples
tutorial-style sessions with application examples on day three
KCDS members as well as doctoral researchers from KIT and other universities/ research centers are welcome to join! There is no participation fee. Please note that KCDS doesn't cover travel and accomodation expenses.
building 20.30, room 0.014
Aretha Teckentrup, Thomas O'Leary-Roseberry
The program includes short courses on the following topics:
Neural Operators: Thomas O'Leary-Roseberry (University of Texas), confirmed.
Gaussian Processes: Aretha Teckentrup (University of Edinburgh), confirmed.
Link between Gaussian Processes and Neural Networks (incl. Neural Operators): Tobias Weber (U Tübingen), confirmed.
Further, you can expect:
poster session and networking dinner on the first day
social event in the evening on the second day
sessions that combine mathematical theory with application and real-life examples
tutorial-style sessions with application examples on day three
KCDS members as well as doctoral researchers from KIT and other universities/ research centers are welcome to join! There is no participation fee. Please note that KCDS doesn't cover travel and accomodation expenses.
building 20.30, room 0.014
Aretha Teckentrup, Thomas O'Leary-Roseberry
The program includes short courses on the following topics:
Neural Operators: Thomas O'Leary-Roseberry (University of Texas), confirmed.
Gaussian Processes: Aretha Teckentrup (University of Edinburgh), confirmed.
Link between Gaussian Processes and Neural Networks (incl. Neural Operators): Tobias Weber (U Tübingen), confirmed.
Further, you can expect:
poster session and networking dinner on the first day
social event in the evening on the second day
sessions that combine mathematical theory with application and real-life examples
tutorial-style sessions with application examples on day three
KCDS members as well as doctoral researchers from KIT and other universities/ research centers are welcome to join! There is no participation fee. Please note that KCDS doesn't cover travel and accomodation expenses.
KIT, Campus South
20.30 Seminar room 0.014
…
Prof. Dr. Oliver Stein (EBI), Dr.-Ing. Ali Shamooni (Uni Stuttgart)
Challenge
Turbulent flows — the chaotic, swirling motions you see in storm clouds, the wake behind an airplane wing, or the frothy swirls in your morning cup of coffee — span a vast range of interacting scales. Resolving every vortex from meter-wide eddies down to tiny millimeter-scale whirls requires grids with billions of points and supercomputers running for days or weeks. Coarse, low-resolution simulations run quickly but miss critical small-scale physics. The Hack the Turbulence hackathon challenges you to bridge this gap. Develop deep-learning models that take coarse turbulent flow data and reconstruct high-resolution fields, while respecting the underlying physics.
We invite students and researchers from mathematics, data science, engineering, and physics to join us for four days of hands-on innovation. Participants will enhance their skills in data analysis and scientific machine learning. They will also connect with researchers from different disciplines and get hands-on experience with KIT's supercomputer cluster.
This event is organized by machine learning enthusiasts from KCDS, with support from KIT and SCC.
KIT, Campus South
20.30 Seminar room 0.014
…
Prof. Dr. Oliver Stein (EBI), Dr.-Ing. Ali Shamooni (Uni Stuttgart)
Challenge
Turbulent flows — the chaotic, swirling motions you see in storm clouds, the wake behind an airplane wing, or the frothy swirls in your morning cup of coffee — span a vast range of interacting scales. Resolving every vortex from meter-wide eddies down to tiny millimeter-scale whirls requires grids with billions of points and supercomputers running for days or weeks. Coarse, low-resolution simulations run quickly but miss critical small-scale physics. The Hack the Turbulence hackathon challenges you to bridge this gap. Develop deep-learning models that take coarse turbulent flow data and reconstruct high-resolution fields, while respecting the underlying physics.
We invite students and researchers from mathematics, data science, engineering, and physics to join us for four days of hands-on innovation. Participants will enhance their skills in data analysis and scientific machine learning. They will also connect with researchers from different disciplines and get hands-on experience with KIT's supercomputer cluster.
This event is organized by machine learning enthusiasts from KCDS, with support from KIT and SCC.
KIT, Campus South
20.30 Seminar room 0.014
…
Prof. Dr. Oliver Stein (EBI), Dr.-Ing. Ali Shamooni (Uni Stuttgart)
Challenge
Turbulent flows — the chaotic, swirling motions you see in storm clouds, the wake behind an airplane wing, or the frothy swirls in your morning cup of coffee — span a vast range of interacting scales. Resolving every vortex from meter-wide eddies down to tiny millimeter-scale whirls requires grids with billions of points and supercomputers running for days or weeks. Coarse, low-resolution simulations run quickly but miss critical small-scale physics. The Hack the Turbulence hackathon challenges you to bridge this gap. Develop deep-learning models that take coarse turbulent flow data and reconstruct high-resolution fields, while respecting the underlying physics.
We invite students and researchers from mathematics, data science, engineering, and physics to join us for four days of hands-on innovation. Participants will enhance their skills in data analysis and scientific machine learning. They will also connect with researchers from different disciplines and get hands-on experience with KIT's supercomputer cluster.
This event is organized by machine learning enthusiasts from KCDS, with support from KIT and SCC.
KIT, Campus South
20.30 Seminar room 0.014
…
Prof. Dr. Oliver Stein (EBI), Dr.-Ing. Ali Shamooni (Uni Stuttgart)
Challenge
Turbulent flows — the chaotic, swirling motions you see in storm clouds, the wake behind an airplane wing, or the frothy swirls in your morning cup of coffee — span a vast range of interacting scales. Resolving every vortex from meter-wide eddies down to tiny millimeter-scale whirls requires grids with billions of points and supercomputers running for days or weeks. Coarse, low-resolution simulations run quickly but miss critical small-scale physics. The Hack the Turbulence hackathon challenges you to bridge this gap. Develop deep-learning models that take coarse turbulent flow data and reconstruct high-resolution fields, while respecting the underlying physics.
We invite students and researchers from mathematics, data science, engineering, and physics to join us for four days of hands-on innovation. Participants will enhance their skills in data analysis and scientific machine learning. They will also connect with researchers from different disciplines and get hands-on experience with KIT's supercomputer cluster.
This event is organized by machine learning enthusiasts from KCDS, with support from KIT and SCC.
+49 721 608-47748
angela huehnerfuss ∂does-not-exist.kit edu
www.kcds.kit.edu/