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Alexander Novikov, Maxim Rakhuba, Ivan Oseledets
Automatic Differentiation for Riemannian Optimization on Low-Rank Matrix and Tensor-Train Manifolds
Article in SIAM Journal on Scientific Computing, 2022
Application Area:
Riemanian Optimization
Tools:
T3F
Mustafa Bandukwala2021VoP
Viability of Power-Split Hybrid-Electric Aircraft under Robust Control Co-Design
Master thesis, Department of Mechanical and Materials Engineering, University of Cincinnati, 2021
Application Area:
Aerodynamics
Tools:
ADiMat
Andrea Maggi, Dominik Garmatter, Sebastian Sager, Martin Stoll, Kai Sundmacher
Power-to-Syngas: A Parareal Optimal Control Approach
Article in Frontiers in Energy Research, 2021
Application Area:
Chemistry
Tools:
ADiMat
Henrik Büsing
Challenges in simulation of geological CO_2 sequestration and supercritical geothermal reservoirs
Ph.D. thesis, RWTH Aachen University, 2021
Application Area:
Geophysics
Tools:
ADiMat, TAPENADE
Yuxuan Jing, Rami M. Younis
Cache-Aware and Roofline-Ideal Automatic Differentiation
2021
Application Area:
Reservoir Simulation
Tools:
MXCSL
Johannes Blühdorn, Nicolas R. Gauger, Matthias Kabel
AutoMat: automatic differentiation for generalized standard materials on GPUs
Article in Computational Mechanics, 2021
Application Area:
Material Science, Mechanical Engineering, Ordinary Differential Equations
Theory & Techniques:
Forward Mode, Parallelism, Performance, Reverse Mode
William S. Moses, Valentin Churavy, Ludger Paehler, Jan Hückelheim, Sri Hari Krishna Narayanan, Michel Schanen, Johannes Doerfert
Reverse-Mode Automatic Differentiation and Optimization of GPU Kernels via Enzyme
Conference proceeding, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, Association for Computing Machinery, 2021
Tools:
Enzyme
Theory & Techniques:
Parallelism
Jan Hückelheim, Johannes Doerfert
Spray: Sparse Reductions of Arrays in OpenMP
Conference proceeding, 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2021
Theory & Techniques:
Parallelism
A. Griewank, T. Streubel, C. Tischendorf
On the abs-polynomial expansion of piecewise smooth functions
Article in Optimization Methods & Software, Taylor & Francis, 2021
Theory & Techniques:
Piecewise Linear
Saeed Azad, Michael J. Alexander-Ramos
Robust Combined Design and Control Optimization of Hybrid-Electric Vehicles Using MDSDO
Article in IEEE Transactions on Vehicular Technology, 2021
Application Area:
Electric Vehicle Powertrain
Tools:
ADiMat
Hong Zhang, Emil Constantinescu
Revolve-Based Adjoint Checkpointing for Multistage Time Integration
Conference proceeding, Computational Science -- ICCS 2021, Springer International Publishing, 2021
Theory & Techniques:
Checkpointing
Rebecca Hyen Hae Kim
Dynamic Optimization Algorithms for Baseload Power Plant Cycling under Variable Renewable Energy
Ph.D. thesis, Department of Chemical and Biomedical Engineering, West Virginia University, 2021
Application Area:
Chemistry, Dynamic Optimization
Tools:
ADiMat
N. McGreivy, S. R. Hudson, C. Zhu
Optimized finite-build stellarator coils using automatic differentiation
Article in Nuclear Fusion, IOP Publishing, 2021
Application Area:
Nuclear Fusion
Tools:
JAX
Adam S. Abbott, Boyi Z. Abbott, Justin M. Turney, Henry F. Schaefer
Arbitrary-Order Derivatives of Quantum Chemical Methods via Automatic Differentiation
Article in The Journal of Physical Chemistry Letters, American Chemical Society (ACS), 2021
Application Area:
Chemistry
Tools:
JAX
Dominik Garmatter, Andrea Maggi, Marcus Wenzel, Shaimaa Monem, Mirko Hahn, Martin Stoll, Sebastian Sager, Peter Benner, Kai Sundmacher
Power-to-Chemicals: A Superstructure Problem for Sustainable Syngas Production
Mathematical Modeling, Simulation and Optimization for Power Engineering and Management, Springer International Publishing, 2021
Application Area:
Chemistry
Tools:
ADiMat
Lu Lu, Xuhui Meng, Zhiping Mao, George Em Karniadakis
DeepXDE: A Deep Learning Library for Solving Differential Equations
Article in SIAM Review, 2021
Application Area:
Machine Learning
Tim Kaler, Tao B. Schardl, Brian Xie, Charles E. Leiserson, Jie Chen, Aldo Pareja, Georgios Kollias
PARAD: A Work-Efficient Parallel Algorithm for Reverse-Mode Automatic Differentiation
Conference proceeding, Proceedings of the Symposium on Algorithmic Principles of Computer Systems (APOCS), Society for Industrial and Applied Mathematics, 2021
Theory & Techniques:
Parallelism, Reverse Mode
Belmiro P. M. Duarte, Anthony C. Atkinson, José F. O. Granjo, Nuno M. C. Oliveira
A model-based framework assisting the design of vapor-liquid equilibrium experimental plans
Article in Computers & Chemical Engineering, 2021
Application Area:
Chemistry
Tools:
ADiMat
Jorge López, Cosmin Anitescu, Timon Rabczuk
Isogeometric structural shape optimization using automatic sensitivity analysis
Article in Applied Mathematical Modelling, 2021
Application Area:
Shape optimization
Tools:
ADiMat
Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov, Ivan Oseledets
Tensor Train Decomposition on TensorFlow (T3F)
Article in Journal of Machine Learning Research, 2020
Tools:
T3F

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