Racah Polynomial

Racah polynomials are orthogonal polynomials with applications in diverse fields, including signal processing and image analysis. Current research focuses on improving the computational efficiency and numerical stability of Racah polynomial calculations, particularly for higher-order moments, employing techniques like improved stabilization algorithms and leveraging deep learning models for efficient matrix inversions. These advancements enhance the applicability of Racah polynomials in areas such as massive MIMO systems and knot theory, where they provide powerful tools for analysis and computation.

Papers

November 17, 2024

RPN 2: On Interdependence Function Learning Towards Unifying and Advancing CNN, RNN, GNN, and Transformer
Jiawei Zhang
Transformer Based Gene Level GNN CNN Network \Sigma}{\Delta}$ Low Pas RNN Backbone Fine Tuning Interdependent Network Structure Function Polynomial Network Racah Polynomial

October 15, 2024

Experimental Design Using Interlacing Polynomials
Lap Chi Lau, Robert Wang, Hong Zhou
Unified Framework Experimental Design Approximation Guarantee Approximation Method Design Problem Racah Polynomial

February 19, 2024

Truncated Polynomial Expansion-Based Detection in Massive MIMO: A Model-Driven Deep Learning Approach
Kazem Izadinasab, Ahmed Wagdy Shaban, Oussama Damen
Multiple Input Multiple Output Massive MIMO Large Matrix Polynomial Expansion Model Driven Deep Linear Object Detection Racah Polynomial

December 30, 2022

Accelerated and Improved Stabilization for High Order Moments of Racah Polynomials
Basheera M. Mahmmod, Sadiq H. Abdulhussain, Tomáš Suk
Low Rate ACCELERATION Order Moment Polynomial Basis Orthogonal Moment Racah Polynomial

November 30, 2021

Learning knot invariants across dimensions
Jessica Craven, Mark Hughes, Vishnu Jejjala, Arjun Kar
Box Dimension Dynamical Invariant Knot Theory Knot Invariant Racah Polynomial

Racah Polynomial

Papers

RPN 2: On Interdependence Function Learning Towards Unifying and Advancing CNN, RNN, GNN, and Transformer

Experimental Design Using Interlacing Polynomials

Truncated Polynomial Expansion-Based Detection in Massive MIMO: A Model-Driven Deep Learning Approach

Accelerated and Improved Stabilization for High Order Moments of Racah Polynomials

Learning knot invariants across dimensions