9 citations · 15 across the 14 of their papers we have counts for
9 papers · 1 filter
Quantum-Inspired Hybrid Neural Networks for Neural Decoding: A Controlled Ablation Study of Learnable Quantum Sidecar Integration
Diana Legziel Levy, Menachem Finkelstein, Peter Chin +2
We study parameterized quantum circuits (PQCs) integrated as residual sidecar modules within a ResNet-50 backbone for 31-class neural population decoding---imagined handwriting cla…
Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes
Quang Truong, Peter Chin
Graph Neural Networks (GNNs), despite achieving remarkable performance across different tasks, are theoretically bounded by the 1-Weisfeiler-Lehman test, resulting in limitations i…
cs-net: structural approach to time-series forecasting for high-dimensional feature space data with limited observations
Weiyu Zong, Mingqian Feng, Griffin Heyrich +1
In recent years, deep-learning-based approaches have been introduced to solving time-series forecasting-related problems. These novel methods have demonstrated impressive performan…
A Multi-scale Graph Signature for Persistence Diagrams based on Return Probabilities of Random Walks
Chau Pham, Trung Dang, Peter Chin
Persistence diagrams (PDs), often characterized as sets of death and birth of homology class, have been known for providing a topological representation of a graph structure, which…
Collusion Detection in Team-Based Multiplayer Games
Laura Greige, Fernando De Mesentier Silva, Meredith Trotter +3
In the context of competitive multiplayer games, collusion happens when two or more teams decide to collaborate towards a common goal, with the intention of gaining an unfair advan…
Non-Volatile Memory Accelerated Geometric Multi-Scale Resolution Analysis
Andrew Wood, Moshik Hershcovitch, Daniel Waddington +5
Dimensionality reduction algorithms are standard tools in a researcher's toolbox. Dimensionality reduction algorithms are frequently used to augment downstream tasks such as machin…