6 papers
Robust Reasoning and Learning with Brain-Inspired Representations under Hardware-Induced Nonlinearities
William Youngwoo Chung, Hamza Errahmouni Barkam, Tamoghno Das +1
Traditional machine learning depends on high-precision arithmetic and near-ideal hardware assumptions, which is increasingly challenged by variability in aggressively scaled semico…
MERIT: Multi-domain Efficient RAW Image Translation
Wenjun Huang, Shenghao Fu, Yian Jin +10
RAW images captured by different camera sensors exhibit substantial domain shifts due to varying spectral responses, noise characteristics, and tone behaviors, complicating their d…
Geometric Priors for Generalizable World Models via Vector Symbolic Architecture
William Youngwoo Chung, Calvin Yeung, Hansen Jin Lillemark +3
A key challenge in artificial intelligence and neuroscience is understanding how neural systems learn representations that capture the underlying dynamics of the world. Most world…
Encoder-Free Knowledge-Graph Reasoning with LLMs via Hyperdimensional Path Retrieval
Yezi Liu, William Youngwoo Chung, Hanning Chen +2
Recent progress in large language models (LLMs) has made knowledge-grounded reasoning increasingly practical, yet KG-based QA systems often pay a steep price in efficiency and tran…
Mitigating Bias in Graph Hyperdimensional Computing
Yezi Liu, William Youngwoo Chung, Yang Ni +2
Graph hyperdimensional computing (HDC) has emerged as a promising paradigm for cognitive tasks, emulating brain-like computation with high-dimensional vectors known as hypervectors…
Continuous GNN-based Anomaly Detection on Edge using Efficient Adaptive Knowledge Graph Learning
Sanggeon Yun, Ryozo Masukawa, William Youngwoo Chung +3
The increasing demand for robust security solutions across various industries has made Video Anomaly Detection (VAD) a critical task in applications such as intelligent surveillanc…