133 citations · 300 across the 26 of their papers we have counts for
27 papers
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…
CDGP: Contrastive Dual Gaussian Processes for Weakly Supervised Anomaly Segmentation
Seungjun Chu, Seokhee Han, Mateusz Nowak +1
Industrial visual inspection must both decide whether a product is defective and localize the defect, yet pixel-level masks are costly to collect at scale. Most anomaly-segmentatio…
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…
Bridging Neural and Symbolic Representations with Transitional Dictionary Learning
Junyan Cheng, Peter Chin
This paper introduces a novel Transitional Dictionary Learning (TDL) framework that can implicitly learn symbolic knowledge, such as visual parts and relations, by reconstructing t…
Adversarial Transformer Language Models for Contextual Commonsense Inference
Pedro Colon-Hernandez, Henry Lieberman, Yida Xin +3
Contextualized or discourse aware commonsense inference is the task of generating coherent commonsense assertions (i.e., facts) from a given story, and a particular sentence from t…
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…