Summary of Fully Distributed Online Training Of Graph Neural Networks in Networked Systems, by Rostyslav Olshevskyi et al.
Fully Distributed Online Training of Graph Neural Networks in Networked Systemsby Rostyslav Olshevskyi, Zhongyuan Zhao,…
Summary of Two-way Deconfounder For Off-policy Evaluation in Causal Reinforcement Learning, by Shuguang Yu et al.
Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learningby Shuguang Yu, Shuxing Fang, Ruixin Peng,…
Summary of Kernel Stochastic Configuration Networks For Nonlinear Regression, by Yongxuan Chen and Dianhui Wang
Kernel Stochastic Configuration Networks for Nonlinear Regressionby Yongxuan Chen, Dianhui WangFirst submitted to arxiv on:…
Summary of Proximal Iteration For Nonlinear Adaptive Lasso, by Nathan Wycoff et al.
Proximal Iteration for Nonlinear Adaptive Lassoby Nathan Wycoff, Lisa O. Singh, Ali Arab, Katharine M.…
Summary of No Free Lunch From Random Feature Ensembles, by Benjamin S. Ruben et al.
No Free Lunch From Random Feature Ensemblesby Benjamin S. Ruben, William L. Tong, Hamza Tahir…
Summary of Data-driven, Parameterized Reduced-order Models For Predicting Distortion in Metal 3d Printing, by Indu Kant Deo et al.
Data-Driven, Parameterized Reduced-order Models for Predicting Distortion in Metal 3D Printingby Indu Kant Deo, Youngsoo…
Summary of Deep Causal Inference For Point-referenced Spatial Data with Continuous Treatments, by Ziyang Jiang et al.
Deep Causal Inference for Point-referenced Spatial Data with Continuous Treatmentsby Ziyang Jiang, Zach Calhoun, Yiling…
Summary of Graph Neural Networks Need Cluster-normalize-activate Modules, by Arseny Skryagin et al.
Graph Neural Networks Need Cluster-Normalize-Activate Modulesby Arseny Skryagin, Felix Divo, Mohammad Amin Ali, Devendra Singh…
Summary of Asymptotics Of Linear Regression with Linearly Dependent Data, by Behrad Moniri and Hamed Hassani
Asymptotics of Linear Regression with Linearly Dependent Databy Behrad Moniri, Hamed HassaniFirst submitted to arxiv…
Summary of Self-test Loss Functions For Learning Weak-form Operators and Gradient Flows, by Yuan Gao et al.
Self-test loss functions for learning weak-form operators and gradient flowsby Yuan Gao, Quanjun Lang, Fei…