SC Seminar: Shalini Shalini

Shalini Shalini, TU Kaiserslautern Title: Sparse Deep Neural Network and Hyperparameter Optimization Abstract: Despite the considerable success of deep learning in recent years, it is still challenging to deploy state-of-the-art deep neural networks due to the high computational and memory … Continue reading

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SC Seminar: Kavyashree Renukachari

Kavyashree Renukachari, TU Kaiserslautern Title: Estimation of Critical Batch Sizes for Distributed Deep Learning Abstract: The applications of Deep Learning in various domains is increasing, and so is the size of the dataset and the complexity of the model used … Continue reading

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SC Seminar: Angel Adrian Rojas Jimenez

Angel Adrian Rojas Jimenez, TU Kaiserslautern Title: On the stochastic global optimization and numerical implementation for classification problems Abstract: Dynamic search trajectories like B.T. Polyak’s heavy ball method have been implemented in order to speed up the convergence rate to … Continue reading

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SC Seminar: Avraam Chatzimichailidis

Avraam Chatzimichailidis, Fraunhofer ITWM, Kaiserslautern Title: Second-Order Methods for Neural Networks/Bridging the Gap between Neural Network Pruning and Neural Architecture Search Abstract: Optimization in deep learning is still dominated by first-order gradient methods, such as stochastic gradient descent. Second-order optimization … Continue reading

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SC Seminar: Mathias J. Krause

Dr. Mathias J. Krause, Lattice Boltzmann Research Group, Karlsruher Institut für Technologie (KIT) Title: Fluid Flow Optimization with Lattice Boltzmann Methods with Applications Abstract: For many medical as well as technical applications the accurate knowledge of fluid flow dynamics, e.g. … Continue reading

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SC Seminar: Jan Rottmayer

Jan Rottmayer, TU Kaiserslautern Title: Reduced Order Modeling and Nonlinear System Identification Techniques for Fluid Dynamics Abstract: Data-driven mathematical methods are increasingly important for characterizing complex dynamical systems across the physical and engineering domain. These methods discover and exploit a … Continue reading

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SC Seminar: Félix Givois

Félix Givois, Fraunhofer ITWM, Kaiserslautern Title: Quantum Computing for Material Characterization Abstract: The description of material laws of a complex microstructure is a problem really complex to solve. As there is not any analytical description of it,the best method is … Continue reading

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SC Seminar: Paula Harder

Paula Harder, Fraunhofer ITWM, Kaiserslautern Title: Emulating Aerosol Microphysics with Machine Learning Abstract: Aerosol particles play an important role in the climate system by absorbing and scattering radiation and by influencing cloud properties. They are also one of the biggest … Continue reading

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SC Seminar: Johannes Blühdorn

Johannes Blühdorn, Chair for Scientific Computing, TU Kaiserslautern Title: OpDiLib, an Open Multiprocessing Differentiation Library Abstract: Automatic differentiation (AD) comprises techniques and tools for acquiring machine-accurate derivatives of computer codes. AD has a long history of successful applications in areas … Continue reading

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SC Seminar: Raju Ram

Raju Ram, Fraunhofer ITWM, Kaiserslautern Title: Hybrid parallel ILU preconditioner to solve sparse linear systems Abstract: The solution of large sparse linear systems is a ubiquitous problem in chemistry, physics, and engineering applications. Krylov subspace methods are preferred to solve … Continue reading

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