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The explosion of spatiotemporal data in the physical world requires new deep learning tools to model complex dynamical systems.
In the wake of natural disasters, survivors’ losses of education and lifetime earnings may be comparable to the cost of property damage, according to a new study in Nature Human Behaviour co-authored ...
Despite widespread use in online transactions, rating systems only provide summary statistics of buyers' diverse opinions at best. To investigate the consequences of this coarse form of information ag...
本报告介绍我们近期的两项工作。(1) 求解PDE的PINN方法在处理时间发展方程时往往遇到难以收敛的困难。我们发展了时间方向的预训练PINN方法及自适应步长方法,解决了收敛性困难,使PDE求解精度能够得到系统性提高。我们在一系列时间发展方程上获得了比文献报道更精确的训练结果。(2) 辐射调源问题是一个典型的反问题,要求调整辐射输运方程的边条件(源),使解满足特定设计目标。我们针对辐射输运方程的时序...
Differential privacy is one of the most common techniques in privacy-preserving machine learning due to its rigorous math definition and theoretical results. Transfer learning and Federated learning a...
In this talk, I will present our recent work on the convergence/generalization analysis for the popular optimizers in deep learning. (1) We establish the convergence for Adam under (L0,L1 ) smoothness...
A fundamental problem from computational learning theory is to well-reconstruct an unknown function on the discrete hypercubes. One classical result of this problem for the random query model is the l...
MIT undergraduates are learning about nanoscale science and engineering from individual atoms up to full-scale functional systems, and they’re doing it hands-on at MIT.nano.
This report consists of two parts associated with graph neural networks: generalization and graph structural learning. We first study the Rademacher complexity of GNNs, as one of independent-algorithm...
2023年2月25日,农学院智慧农业团队在《Science of The Total Environment》期刊发表了题为“Improving the spatial and temporal estimation of ecosystem respiration using multi-source data and machine learning methods in a rainfed ...
Tool path planning is a crucial factor of computer-aided design and manufacturing (CAD/CAM). To generate suitable tool paths, the previous methods often transform the problem into local or global opti...
Solving multi-scale PDEs is difficult in high-dimensional and/or convection-dominant cases. The interacting particle methods (IPM) are shown to outperform solving PDEs directly. Examples include compu...
System optimization and control have become the key design philosophies in modern control system theories, where reinforcement learning (RL) algorithm has drawn considerable attention in recent litera...
Nonlinear modelling of dynamic spatio-temporal network data is often a challenge with various issues, in particular due to irregularly observed locations and location-wide non-stationarity. In this pa...
Electronic health records (EHR) have provided a great opportunity to exploit personalized health data to optimize clinical decision making and achieve personalized treatment recommendation. In this ta...

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