Summary of Scaling and Renormalization in High-dimensional Regression, by Alexander Atanasov et al.
Scaling and renormalization in high-dimensional regressionby Alexander Atanasov, Jacob A. Zavatone-Veth, Cengiz PehlevanFirst submitted to…
Scaling and renormalization in high-dimensional regressionby Alexander Atanasov, Jacob A. Zavatone-Veth, Cengiz PehlevanFirst submitted to…
WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecastingby Theodoros Theodoropoulos, Angelos-Christos…
Discovering robust biomarkers of psychiatric disorders from resting-state functional MRI via graph neural networks: A…
M-DEW: Extending Dynamic Ensemble Weighting to Handle Missing Valuesby Adam Catto, Nan Jia, Ansaf Salleb-Aouissi,…
Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Designby…
A Logic for Reasoning About Aggregate-Combine Graph Neural Networksby Pierre Nunn, Marco Sälzer, François Schwarzentruber,…
Block-As-Domain Adaptation for Workload Prediction from fNIRS Databy Jiyang Wang, Ayse Altay, Senem VelipasalarFirst submitted…
GMC-PINNs: A new general Monte Carlo PINNs method for solving fractional partial differential equations on…
Graphical Reasoning: LLM-based Semi-Open Relation Extractionby Yicheng Tao, Yiqun Wang, Longju BaiFirst submitted to arxiv…
Machine Learning-based Estimation of Respiratory Fluctuations in a Healthy Adult Population using BOLD fMRI and…