SEMINARS
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INS Colloquia
Thermodynamic Machine Learning Through Maximum Work Production
- Alec Boyd, University of California at Davis
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2020.09.22, 10:00-11:00
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INS Colloquia
Machine Learning for Quantum Control
- Barry Sanders，University of Calgary
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2020.09.08, 10:00-11:00
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INS Colloquia
Higher Order Energy Stable ETD Based Methods for Gradient Flows
- Xiaoming Wang, Southern University of Science and Technology
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2020.08.11, 14:00-15:00
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Young Scholars' Forum
Landscape Analysis of Non-Convex Optimizations in Phase Retrieval
- Jianfeng Cai, Hong Kong University of Science and Technology
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2020.07.15, 14:00-15:00
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Young Scholars' Forum
How Neural Network can Learn to Denoise an Image without any Training Data
- Hui Ji, National University of Singapore, Singapore
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2020.07.08, 14:00-15:00
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INS Colloquia
Machine Learning, Adaptive Numerical Approximation and VOF Methods
- Bruno Després, Sorbonne University and IUF, Paris, France
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2020.07.07, 16:00-17:00
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INS Colloquia
A Geometric Understanding of Deep Learning
- Xianfeng Gu, Stony Brook University, USA
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2020.07.03, 09:00-10:00
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INS Colloquia
Generalized Law of Mass Action (LMA) with Energetic Variational Approaches (EnVarA)
- Chun Liu, Illinois Institute of Technology, USA
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2020.06.30, 10:00-11:00
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Data Science Seminars
A Statistical Mechanics Theory of Generalization in Kernel Regression and Wide Neural Networks
- Cengiz Pehlevan, Harvard University
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2020.06.26, 10:00-11:00
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Young Scholars' Forum
The Weak Galerkin Finite Element Method for Eigenvalue Problems
- Ran Zhang, Jilin University, China
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2020.06.24, 14:00-15:00
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Distinguished Lectures in Natural Sciences
Nonlinear Aggregation-Diffusion Equations: Gradient Flows, Free Energies and Phase Transitions
- Jose Carrillo, University of Oxford, UK
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2020.06.23, 16:00-17:00
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Distinguished Lectures in Natural Sciences
Generic Regularity in Obstacle Problems
- Alessio Figalli, ETH-Zürich, Switzerland
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2020.06.19, 16:00-17:00
