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Publication search results
found 96 matches
- 2024
- Umesh Vaidya, Duvan Tellez-Castro:
Data-Driven Stochastic Optimal Control With Safety Constraints Using Linear Transfer Operators. IEEE Trans. Autom. Control. 69(4): 2100-2115 (2024) - Florian Beier, Hancheng Bi, Clément Sarrazin, Bernhard Schmitzer, Gabriele Steidl:
Transfer Operators from Batches of Unpaired Points via Entropic Transport Kernels. CoRR abs/2402.08425 (2024) - 2023
- Christof Schütte, Stefan Klus, Carsten Hartmann:
Overcoming the timescale barrier in molecular dynamics: Transfer operators, variational principles and machine learning. Acta Numer. 32: 517-673 (2023) - Joseph Moyalan, Hyungjin Choi, Yongxin Chen, Umesh Vaidya:
Data-driven optimal control via linear transfer operators: A convex approach. Autom. 150: 110841 (2023) - Mohammed Yousef Salem Ali, Mohammed Jabreel, Aïda Valls, Marc Baget, Mohamed Abdel-Nasser:
Glaucoma Detection in Retinal Fundus Images Based on Deep Transfer Learning and Fuzzy Aggregation Operators. Int. J. Artif. Intell. Tools 32(2): 2340001:1-2340001:28 (2023) - Andrea de Giorgio, Malvina Roci, Antonio Maffei, Milan Jocevski, Mauro Onori, Lihui Wang:
Measuring the effect of automatically authored video aid on assembly time for procedural knowledge transfer among operators in adaptive assembly stations. Int. J. Prod. Res. 61(12): 3910-3925 (2023) - Xiaoliang Ma, Mingyu Xu, Yanan Yu, Hongjie Liu, Yan Wang, Lei Wang, Yutao Qi, Jian Xiong:
Enhancing evolutionary multitasking optimization by leveraging inter-task knowledge transfers and improved evolutionary operators. Knowl. Based Syst. 259: 110027 (2023) - Joseph Moyalan, Yongxin Chen, Umesh Vaidya:
Convex Approach to Data-Driven Off-Road Navigation via Linear Transfer Operators. IEEE Robotics Autom. Lett. 8(6): 3278-3285 (2023) - Yixuan Sun, Christian Moya, Guang Lin, Meng Yue:
DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-Shot Transfer the Dynamic Response of Networked Systems. IEEE Syst. J. 17(3): 4360-4370 (2023) - Mengjiang Liu, Qianhong Wu, Kun Wang, Tianxu Han, Yiming Hei:
Cross-chain based Spectrum Resources Transfer Technology across Different Telecom Operators Towards 6G. Blockchain 2023: 365-369 - Mathias Schreiner, Ole Winther, Simon Olsson:
Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics. NeurIPS 2023 - Florian Beier:
Gromov-Wasserstein Transfer Operators. SSVM 2023: 614-626 - Yanfang Lyu, Xiaoyu Zhao, Zhiqiang Gong, Xiao Kang, Wen Yao:
Multi-fidelity prediction of fluid flow and temperature field based on transfer learning using Fourier Neural Operator. CoRR abs/2304.06972 (2023) - Joseph Moyalan, Andrew Zheng, Sriram S. K. S. Narayanan, Umesh Vaidya:
Off-Road Navigation of Legged Robots Using Linear Transfer Operators. CoRR abs/2305.02938 (2023) - Stefan Klus, Maia Trower:
Transfer operators on graphs: Spectral clustering and beyond. CoRR abs/2305.11766 (2023) - Ben S. Southworth, Thomas A. Manteuffel:
On Compatible Transfer Operators in Nonsymmetric Algebraic Multigrid. CoRR abs/2307.05900 (2023) - Jake Buzhardt, Phanindra Tallapragada:
Controlled density transport by microrotors in a Stokes flow using linear transfer operators. CoRR abs/2310.17832 (2023) - 2022
- Rafet Durgut, Mehmet Emin Aydin, Abdur Rakib:
Transfer Learning for Operator Selection: A Reinforcement Learning Approach. Algorithms 15(1): 24 (2022) - Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis:
Deep transfer operator learning for partial differential equations under conditional shift. Nat. Mac. Intell. 4(12): 1155-1164 (2022) - Heyang Thomas Li, Zachary Todd, Nikolas Bielski, Felix Carroll:
3D lidar point-cloud projection operator and transfer machine learning for effective road surface features detection and segmentation. Vis. Comput. 38(5): 1759-1774 (2022) - Harshad Deshmukh, Bruhathi Sundarmurthy, Jignesh M. Patel:
On inter-operator data transfers in query processing. ICDE 2022: 820-832 - Zhichun Huang, Rudrasis Chakraborty, Vikas Singh:
Forward Operator Estimation in Generative Models with Kernel Transfer Operators. ICML 2022: 9148-9172 - Ziyang Tang, Yihao Feng, Qiang Liu:
Operator Deep Q-Learning: Zero-Shot Reward Transferring in Reinforcement Learning. CoRR abs/2201.00236 (2022) - Umesh Vaidya, Duvan Tellez-Castro:
Data-Driven Stochastic Optimal Control using Linear Transfer Operators. CoRR abs/2202.01387 (2022) - Joseph Moyalan, Hyungjin Choi, Yongxin Chen, Umesh Vaidya:
Data-Driven Optimal Control via Linear Transfer Operators: A Convex Approach. CoRR abs/2202.01856 (2022) - Oliver Junge, Daniel Matthes, Bernhard Schmitzer:
Entropic transfer operators. CoRR abs/2204.04901 (2022) - Enrui Zhang, Adar Kahana, Eli Turkel, Rishikesh Ranade, Jay Pathak, George Em Karniadakis:
A Hybrid Iterative Numerical Transferable Solver (HINTS) for PDEs Based on Deep Operator Network and Relaxation Methods. CoRR abs/2208.13273 (2022) - Yixuan Sun, Christian Moya, Guang Lin, Meng Yue:
DeepGraphONet: A Deep Graph Operator Network to Learn and Zero-shot Transfer the Dynamic Response of Networked Systems. CoRR abs/2209.10622 (2022) - Joseph Moyalan, Yongxin Chen, Umesh Vaidya:
Data-Driven Convex Approach to Off-road Navigation via Linear Transfer Operators. CoRR abs/2210.00723 (2022) - Sudam Surasinghe, Jeremie Fish, Erik M. Bollt:
Learning Transfer Operators by Kernel Density Estimation. CoRR abs/2210.03124 (2022)
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