Summary of Learning to Optimize For Mixed-integer Non-linear Programming, by Bo Tang et al.
Learning to Optimize for Mixed-Integer Non-linear Programmingby Bo Tang, Elias B. Khalil, Ján DrgoňaFirst submitted…
Learning to Optimize for Mixed-Integer Non-linear Programmingby Bo Tang, Elias B. Khalil, Ján DrgoňaFirst submitted…
Real-Time Localization and Bimodal Point Pattern Analysis of Palms Using UAV Imageryby Kangning Cui, Wei…
An Explainable AI Model for Predicting the Recurrence of Differentiated Thyroid Cancerby Mohammad Al-Sayed Ahmad,…
Towards Better Multi-head Attention via Channel-wise Sample Permutationby Shen Yuan, Hongteng XuFirst submitted to arxiv…
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysisby Weronika…
TopoFR: A Closer Look at Topology Alignment on Face Recognitionby Jun Dan, Yang Liu, Jiankang…
Early Diagnosis of Acute Lymphoblastic Leukemia Using YOLOv8 and YOLOv11 Deep Learning Modelsby Alaa Awad,…
Information propagation dynamics in Deep Graph Networksby Alessio GravinaFirst submitted to arxiv on: 14 Oct…
Comparison of deep learning and conventional methods for disease onset predictionby Luis H. John, Chungsoo…
A Kernelizable Primal-Dual Formulation of the Multilinear Singular Value Decompositionby Frederiek Wesel, Kim BatselierFirst submitted…