Search Results for author: Jiali Wang

Found 8 papers, 2 papers with code

Humans-in-the-Building: Getting Rid of Thermostats for Optimal Thermal Comfort Control in Energy Management Systems

no code implementations12 Mar 2024 Jiali Wang, Yang Tang, Luca Schenato

Given the widespread attention to individual thermal comfort, coupled with significant energy-saving potential inherent in energy management systems for optimizing indoor environments, this paper aims to introduce advanced "Humans-in-the-building" control techniques to redefine the paradigm of indoor temperature design.

energy management Management

Federated Linear Bandit Learning via Over-the-Air Computation

no code implementations25 Aug 2023 Jiali Wang, Yuning Jiang, Xin Liu, Ting Wang, Yuanming Shi

In this context, we propose a customized federated linear bandits scheme, where each device transmits an analog signal, and the server receives a superposition of these signals distorted by channel noise.

TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones

no code implementations28 Jul 2023 Lin Yan, Hanqi Guo, Thomas Peterka, Bei Wang, Jiali Wang

In comparison with the observed tracks, we demonstrate that TROPHY can capture TC characteristics that are comparable to and sometimes even better than a well-validated TC tracking algorithm that requires multiple dynamic and thermodynamic scalar fields.

Computational Efficiency feature selection +1

Green Federated Learning Over Cloud-RAN with Limited Fronthual Capacity and Quantized Neural Networks

no code implementations30 Apr 2023 Jiali Wang, Yijie Mao, Ting Wang, Yuanming Shi

We rigorously develop an energy consumption model for the local training at devices through the use of QNNs and communication models over Cloud-RAN.

Federated Learning

A Deep Learning Approach to Probabilistic Forecasting of Weather

1 code implementation23 Mar 2022 Nick Rittler, Carlo Graziani, Jiali Wang, Rao Kotamarthi

We discuss an approach to probabilistic forecasting based on two chained machine-learning steps: a dimensional reduction step that learns a reduction map of predictor information to a low-dimensional space in a manner designed to preserve information about forecast quantities; and a density estimation step that uses the probabilistic machine learning technique of normalizing flows to compute the joint probability density of reduced predictors and forecast quantities.

BIG-bench Machine Learning Density Estimation +2

Galaxy Clusters from the DESI Legacy Imaging Surveys. I. Cluster Detection

no code implementations29 Jan 2021 Hu Zou, Jinghua Gao, Xin Xu, Xu Zhou, Jun Ma, Zhimin Zhou, Tianmeng Zhang, Jundan Nie, Jiali Wang, Suijian Xue

Based on the photometric redshift catalog of Zou H. et al. (2019), we apply a fast clustering algorithm to identify 540, 432 galaxy clusters at $z\lesssim1$ in the DESI legacy imaging surveys, which cover a sky area of about 20, 000 deg$^2$.

Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics

Fast and accurate learned multiresolution dynamical downscaling for precipitation

1 code implementation18 Jan 2021 Jiali Wang, Zhengchun Liu, Ian Foster, Won Chang, Rajkumar Kettimuthu, Rao Kotamarthi

We compare the four new CNN-derived high-resolution precipitation results with precipitation generated from original high resolution simulations, a bilinear interpolater and the state-of-the-art CNN-based super-resolution (SR) technique.

Generative Adversarial Network Super-Resolution

Fewmatch: Dynamic Prototype Refinement for Semi-Supervised Few-Shot Learning

no code implementations1 Jan 2021 Xu Lan, Steven McDonagh, Shaogang Gong, Jiali Wang, Zhenguo Li, Sarah Parisot

Semi-Supervised Few-shot Learning (SS-FSL) investigates the benefit of incorporating unlabelled data in few-shot settings.

Few-Shot Learning Pseudo Label

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