Search Results for author: Neng Wan

Found 7 papers, 0 papers with code

Simplified Analysis on Filtering Sensitivity Trade-offs in Continuous- and Discrete-Time Systems

no code implementations8 Apr 2022 Neng Wan, Dapeng Li, Lin Song, Naira Hovakimyan

A simplified analysis is performed on the Bode-type filtering sensitivity trade-off integrals, which capture the sensitivity characteristics of the estimate and estimation error with respect to the process input and estimated signal in continuous- and discrete-time linear time-invariant filtering systems.

Transformers for prompt-level EMA non-response prediction

no code implementations1 Nov 2021 Supriya Nagesh, Alexander Moreno, Stephanie M. Carpenter, Jamie Yap, Soujanya Chatterjee, Steven Lloyd Lizotte, Neng Wan, Santosh Kumar, Cho Lam, David W. Wetter, Inbal Nahum-Shani, James M. Rehg

The transformer model achieves a non-response prediction AUC of 0. 77 and is significantly better than classical ML and LSTM-based deep learning models.

Generalization of Safe Optimal Control Actions on Networked Multi-Agent Systems

no code implementations21 Sep 2021 Lin Song, Neng Wan, Aditya Gahlawat, Chuyuan Tao, Naira Hovakimyan, Evangelos A. Theodorou

The control action composition is achieved by taking a weighted mixture of the existing controllers according to the contribution of each component task.

Distributed Algorithms for Linearly-Solvable Optimal Control in Networked Multi-Agent Systems

no code implementations18 Feb 2021 Neng Wan, Aditya Gahlawat, Naira Hovakimyan, Evangelos A. Theodorou, Petros G. Voulgaris

Distributed algorithms for both discrete-time and continuous-time linearly solvable optimal control (LSOC) problems of networked multi-agent systems (MASs) are investigated in this paper.

Cooperative Path Integral Control for Stochastic Multi-Agent Systems

no code implementations30 Sep 2020 Neng Wan, Aditya Gahlawat, Naira Hovakimyan, Evangelos A. Theodorou, Petros G. Voulgaris

Local control actions that rely only on agents' local observations are designed to optimize the joint cost functions of subsystems.

Compositionality of Linearly Solvable Optimal Control in Networked Multi-Agent Systems

no code implementations28 Sep 2020 Lin Song, Neng Wan, Aditya Gahlawat, Naira Hovakimyan, Evangelos A. Theodorou

The proposed approach achieves both the compositionality and optimality of control actions simultaneously within the cooperative MAS framework in both discrete- and continuous-time in a sample-efficient manner, which reduces the burden of re-computation of the optimal control solutions for the new task on the MASs.

f-Divergence Variational Inference

no code implementations NeurIPS 2020 Neng Wan, Dapeng Li, Naira Hovakimyan

This paper introduces the $f$-divergence variational inference ($f$-VI) that generalizes variational inference to all $f$-divergences.

Stochastic Optimization Variational Inference

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