Min Dai | DeepAI

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Featured Co-authors

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156 publications
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∙ 06/29/2023

A Fast Fourier Convolutional Deep Neural Network For Accurate and Explainable Discrimination Of Wheat Yellow Rust And Nitrogen Deficiency From Sentinel-2 Time-Series Data

Accurate and timely detection of plant stress is essential for yield pro...

0 Yue Shi, et al. ∙

∙ 03/09/2023

Meta contrastive label correction for financial time series

Financial applications such as stock price forecasting, usually face an ...

0 Luxuan Yang, et al. ∙

∙ 09/18/2022

Data-driven Step-to-step Dynamics based Adaptive Control for Robust and Versatile Underactuated Bipedal Robotic Walking

This paper presents a framework for synthesizing bipedal robotic walking...

0 Min Dai, et al. ∙

∙ 05/09/2022

Auto-SDE: Learning effective reduced dynamics from data-driven stochastic dynamical systems

Multiscale stochastic dynamical systems have been widely adopted to scie...

20 Lingyu Feng, et al. ∙

∙ 12/09/2021

Nonparametric inference of stochastic differential equations based on the relative entropy rate

The information detection of complex systems from data is currently unde...

0 Min Dai, et al. ∙

∙ 05/04/2021

Episodic Learning for Safe Bipedal Locomotion with Control Barrier Functions and Projection-to-State Safety

This paper combines episodic learning and control barrier functions in t...

0 Noel Csomay-Shanklin, et al. ∙

∙ 04/21/2021

Bipedal Walking on Constrained Footholds: Momentum Regulation via Vertical COM Control

This paper presents an online walking gait synthesis and a feedback cont...

0 Min Dai, et al. ∙

∙ 03/28/2021

Variational inference of the drift function for stochastic differential equations driven by Lévy processes

In this paper, we consider the nonparametric estimation problem of the d...

0 Min Dai, et al. ∙

∙ 02/25/2021

Learning Controller Gains on Bipedal Walking Robots via User Preferences

Experimental demonstration of complex robotic behaviors relies heavily o...

0 Noel Csomay-Shanklin, et al. ∙

∙ 12/24/2020

Memory-Gated Recurrent Networks

The essence of multivariate sequential learning is all about how to extr...

8 Yaquan Zhang, et al. ∙

∙ 01/06/2020

Maximum Likelihood Estimation of Stochastic Differential Equations with Random Effects Driven by Fractional Brownian Motion

Stochastic differential equations and stochastic dynamics are good model...

0 Min Dai, et al. ∙

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