3 citations · 9 across the 18 of their papers we have counts for
18 papers
HyperSpace: A Generalized Framework for Spatial Encoding in Hyperdimensional Representations
Shay Snyder, Andrew Capodieci, David Gorsich +1
Vector Symbolic Architectures (VSAs) provide a well-defined algebraic framework for compositional representations in hyperdimensional spaces. We introduce HyperSpace, an open-sourc…
qFHRR: Rethinking Fourier Holographic Reduced Representations through Quantized Phase and Integer Arithmetic
Shay Snyder, Hamed Poursiami, Maryam Parsa
Fourier Holographic Reduced Representations (FHRR) provide a compositional framework for encoding structured information with complex-valued hypervectors. FHRR rely on floating-poi…
SRMU: Relevance-Gated Updates for Streaming Hyperdimensional Memories
Shay Snyder, Andrew Capodieci, David Gorsich +1
Sequential associative memories (SAMs) are difficult to build and maintain in real-world streaming environments, where observations arrive incrementally over time, have imbalanced…
VS-Graph: Scalable and Efficient Graph Classification Using Hyperdimensional Computing
Hamed Poursiami, Shay Snyder, Guojing Cong +2
Graph classification is a fundamental task in domains ranging from molecular property prediction to materials design. While graph neural networks (GNNs) achieve strong performance…
A Retina-Inspired Pathway to Real-Time Motion Prediction inside Image Sensors for Extreme-Edge Intelligence
Subhradip Chakraborty, Shay Snyder, Md Abdullah-Al Kaiser +3
The ability to predict motion in real time is fundamental to many maneuvering activities in animals, particularly those critical for survival, such as attack and escape responses.…
On the Privacy-Preserving Properties of Spiking Neural Networks with Unique Surrogate Gradients and Quantization Levels
Ayana Moshruba, Shay Snyder, Hamed Poursiami +1
As machine learning models increasingly process sensitive data, understanding their vulnerability to privacy attacks is vital. Membership inference attacks (MIAs) exploit model res…
Generalizable Reinforcement Learning with Biologically Inspired Hyperdimensional Occupancy Grid Maps for Exploration and Goal-Directed Path Planning
Shay Snyder, Ryan Shea, Andrew Capodieci +2
Real-time autonomous systems utilize multi-layer computational frameworks to perform critical tasks such as perception, goal finding, and path planning. Traditional methods impleme…
Spiking Neural Networks as a Controller for Emergent Swarm Agents
Kevin Zhu, Connor Mattson, Shay Snyder +4
Drones which can swarm and loiter in a certain area cost hundreds of dollars, but mosquitos can do the same and are essentially worthless. To control swarms of low-cost robots, res…
Retina-Inspired Object Motion Segmentation for Event-Cameras
Victoria Clerico, Shay Snyder, Arya Lohia +4
Event-cameras have emerged as a revolutionary technology with a high temporal resolution that far surpasses standard active pixel cameras. This technology draws biological inspirat…
Brain Inspired Probabilistic Occupancy Grid Mapping with Vector Symbolic Architectures
Shay Snyder, Andrew Capodieci, David Gorsich +1
Real-time robotic systems require advanced perception, computation, and action capability. However, the main bottleneck in current autonomous systems is the trade-off between compu…
Hardware-Algorithm Re-engineering of Retinal Circuit for Intelligent Object Motion Segmentation
Jason Sinaga, Victoria Clerico, Md Abdullah-Al Kaiser +5
Recent advances in retinal neuroscience have fueled various hardware and algorithmic efforts to develop retina-inspired solutions for computer vision tasks. In this work, we focus…
Exploration of Novel Neuromorphic Methodologies for Materials Applications
Derek Gobin, Shay Snyder, Guojing Cong +3
Many of today's most interesting questions involve understanding and interpreting complex relationships within graph-based structures. For instance, in materials science, predictin…
Parallelized Multi-Agent Bayesian Optimization in Lava
Shay Snyder, Derek Gobin, Victoria Clerico +2
In parallel with the continuously increasing parameter space dimensionality, search and optimization algorithms should support distributed parameter evaluations to reduce cumulativ…
Asynchronous Neuromorphic Optimization with Lava
Shay Snyder, Sumedh R. Risbud, Maryam Parsa
Performing optimization with event-based asynchronous neuromorphic systems presents significant challenges. Intel's neuromorphic computing framework, Lava, offers an abstract appli…
Transductive Spiking Graph Neural Networks for Loihi
Shay Snyder, Victoria Clerico, Guojing Cong +4
Graph neural networks have emerged as a specialized branch of deep learning, designed to address problems where pairwise relations between objects are crucial. Recent advancements…
Zespol: A Lightweight Environment for Training Swarming Agents
Shay Snyder, Kevin Zhu, Ricardo Vega +2
Agent-based modeling (ABM) and simulation have emerged as important tools for studying emergent behaviors, especially in the context of swarming algorithms for robotic systems. Des…
Neuromorphic Bayesian Optimization in Lava
Shay Snyder, Sumedh R. Risbud, Maryam Parsa
The ever-increasing demands of computationally expensive and high-dimensional problems require novel optimization methods to find near-optimal solutions in a reasonable amount of t…
Object Motion Sensitivity: A Bio-inspired Solution to the Ego-motion Problem for Event-based Cameras
Shay Snyder, Hunter Thompson, Md Abdullah-Al Kaiser +3
Neuromorphic (event-based) image sensors draw inspiration from the human-retina to create an electronic device that can process visual stimuli in a way that closely resembles its b…