Most updated arrangement for Friday: see here

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Title: Deep learning meets inverse problems

Session 1

Name of the speaker Title University
Zhi Zhou Identification of Conductivity in Elliptic Equations Using Deep Neural Networks Hong Kong Polytechnic University
Guozhi Dong Optimal Control of RELU Neural Network Informed Partial Differential Equations Central South University
Junxiong Jia Learning Prediction Policy of Prior Measures for Statistical Inverse Problems of PDEs Xi’an Jiaotong University
Marco Inglesia Ensemble Kalman Inversion for shape identification University of Nottingham

Session 2

Name of the speaker Title University
Tim Jahn Early Stopping of Untrained Neural Networks University of Bonn
Sui Tang A Robust Data-Driven Approach for Estimating Non-local Interaction Potential in Aggregation-Diffusion Equations From Noisy Data University of California, Santa Barbara
Lingyun Qiu Robust Full Waveform Inversion: A Source Wavelet Manipulation Perspective Tsinghua University
Tianhao Hu Solving Elliptic Problems With Singular Solutions Using Splitting Technique The Chinese University of Hong Kong

Session 3

Name of the speaker Title University
Ye Zhang Estimating Adsorption Isotherm Parameters in Chromatography via a Virtual Injection Promoting Double Feed-Forward Neural Network SMBU
Yuling Jiao Inversion of Drift in SDE with Deep Learning Wuhan University
Fengru Wang Deep Ritz Method for Optimization With Elliptical Constrains in High Dimensional Space The Chinese University of Hong Kong

Session 4

Name of the speaker Title University
Ruchi Guo Transformer Meets Boundary Value Inverse Problems The Chinese University of Hong Kong
Wenbin Li Convex Neural Networks for Inverse Problems in Imaging Harbin Institute of Technology
Xiliang Lu Current Density Impedance Imaging with PINNs Wuhan University
Dong Wang Efficient Algorithms for Partition Problems The Chinese University of Hong Kong, Shenzhen