12 citations · 21 across the 11 of their papers we have counts for
11 papers
FedQHD: Closed-Form Function-Space Federated Reinforcement Learning
Yuchen Hou, Yongshan Chen, Zhuowen Zou +4
Federated reinforcement learning enables decentralized agents to collaboratively improve policies or value estimates without exchanging raw trajectories. However, FedAvg-style para…
SAFEVPR: Patch-Based Verification with Empirical FDR Control for Cross-Condition Sequence Visual Place Recognition
Ha Sier, Jiaqiang Zhang, Zhuo Zou +2
Sequence-based visual place recognition (VPR) for loop closure and robot relocalization must decide whether the retrieved top-1 candidate should be accepted. Conformal calibration…
Residualized Temporal Sparse Autoencoders for Interpreting Diffusion Models
Calvin Yeung, Prathyush Poduval, Ali Zakeri +2
Text-to-image diffusion models generate images by iterative denoising, so their internal layers produce trajectories of activations rather than single static representations. Spars…
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…
Coupled Inference in Diffusion Models for Semantic Decomposition
Calvin Yeung, Ali Zakeri, Zhuowen Zou +1
Many visual scenes can be described as compositions of latent factors. Effective recognition, reasoning, and editing often require not only forming such compositional representatio…
Hyperdimensional Quantum Factorization
Prathyush Poduval, Zhuowen Zou, Alvaro Velasquez +1
This paper presents a quantum algorithm for efficiently decoding hypervectors, a crucial process in extracting atomic elements from hypervectors - an essential task in Hyperdimensi…
Generalized Holographic Reduced Representations
Calvin Yeung, Zhuowen Zou, SungHeon Jeong +3
Hyperdimensional Computing (HDC) is a computationally and data-efficient paradigm that acts as a bridge between connectionist and symbolic approaches to artificial intelligence (AI…
HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning
Hanning Chen, Yang Ni, Ali Zakeri +7
In recent times, a plethora of hardware accelerators have been put forth for graph learning applications such as vertex classification and graph classification. However, previous w…
HEAL: Brain-inspired Hyperdimensional Efficient Active Learning
Yang Ni, Zhuowen Zou, Wenjun Huang +6
Drawing inspiration from the outstanding learning capability of our human brains, Hyperdimensional Computing (HDC) emerges as a novel computing paradigm, and it leverages high-dime…
Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Framework
Zhuowen Zou, Haleh Alimohamadi, Farhad Imani +2
Recently, brain-inspired computing models have shown great potential to outperform today's deep learning solutions in terms of robustness and energy efficiency. Particularly, Spiki…
MIMHD: Accurate and Efficient Hyperdimensional Inference Using Multi-Bit In-Memory Computing
Arman Kazemi, Mohammad Mehdi Sharifi, Zhuowen Zou +3
Hyperdimensional Computing (HDC) is an emerging computational framework that mimics important brain functions by operating over high-dimensional vectors, called hypervectors (HVs).…