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View article: Parallax indicates simple cue-anchoring in the head-direction system
Parallax indicates simple cue-anchoring in the head-direction system Open
The rodent head-direction (HD) system provides an internal compass for spatial navigation by integrating angular head velocity and anchoring to visual landmarks. A fundamental challenge for this computation is parallax: as the animal moves…
View article: A Grid Cell-Inspired Structured Vector Algebra for Cognitive Maps
A Grid Cell-Inspired Structured Vector Algebra for Cognitive Maps Open
The entorhinal-hippocampal formation is the mammalian brain's navigation system, encoding both physical and abstract spaces via grid cells. This system is well-studied in neuroscience, and its efficiency and versatility make it attractive …
View article: The neurobench framework for benchmarking neuromorphic computing algorithms and systems
The neurobench framework for benchmarking neuromorphic computing algorithms and systems Open
Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it diffic…
View article: Distributed representations enable robust multi-timescale symbolic computation in neuromorphic hardware
Distributed representations enable robust multi-timescale symbolic computation in neuromorphic hardware Open
Programming recurrent spiking neural networks (RSNNs) to robustly perform multi-timescale computation remains a difficult challenge. To address this, we describe a single-shot weight learning scheme to embed robust multi-timescale dynamics…
View article: Accurate Mapping of RNNs on Neuromorphic Hardware with Adaptive Spiking Neurons
Accurate Mapping of RNNs on Neuromorphic Hardware with Adaptive Spiking Neurons Open
Thanks to their parallel and sparse activity features, recurrent neural networks (RNNs) are well-suited for hardware implementation in low-power neuromorphic hardware. However, mapping rate-based RNNs to hardware-compatible spiking neural …
View article: Distributed Representations Enable Robust Multi-Timescale Symbolic Computation in Neuromorphic Hardware
Distributed Representations Enable Robust Multi-Timescale Symbolic Computation in Neuromorphic Hardware Open
Programming recurrent spiking neural networks (RSNNs) to robustly perform multi-timescale computation remains a difficult challenge. To address this, we describe a single-shot weight learning scheme to embed robust multi-timescale dynamics…
View article: Spiking LCA in a Neural Circuit with Dictionary Learning and Synaptic Normalization
Spiking LCA in a Neural Circuit with Dictionary Learning and Synaptic Normalization Open
The Locally Competitive Algorithm (LCA) [17, 18] was put forward as a model of primary visual cortex [14, 17] and has been used extensively as a sparse coding algorithm for multivariate data. LCA has seen implementations on neuromorphic pr…
View article: NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems
NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems Open
Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it diffic…
View article: SEEK: Scoping neuromorphic architecture impact enabling advanced sensing capabilities
SEEK: Scoping neuromorphic architecture impact enabling advanced sensing capabilities Open
Many sensor modalities used for proliferation detection are expanding hyperspectrally, hyperspatially, and hypertemporally. While these assets are often tasked with high-consequence image processing tasks, the significant computational cos…
View article: Visual Odometry with Neuromorphic Resonator Networks
Visual Odometry with Neuromorphic Resonator Networks Open
Visual Odometry (VO) is a method to estimate self-motion of a mobile robot using visual sensors. Unlike odometry based on integrating differential measurements that can accumulate errors, such as inertial sensors or wheel encoders, visual …
View article: Neuromorphic Visual Scene Understanding with Resonator Networks
Neuromorphic Visual Scene Understanding with Resonator Networks Open
Analyzing a visual scene by inferring the configuration of a generative model is widely considered the most flexible and generalizable approach to scene understanding. Yet, one major problem is the computational challenge of the inference …
View article: Sparse Vector Binding on Spiking Neuromorphic Hardware Using Synaptic Delays
Sparse Vector Binding on Spiking Neuromorphic Hardware Using Synaptic Delays Open
Vector Symbolic Architectures (VSA) were first proposed as connectionist models for symbolic reasoning, leveraging parallel and in-memory computing in brains and neuromorphic hardware that enable low-power, low-latency applications. Symbol…
View article: Neuromorphic Backpropagation Algorithm Software
Neuromorphic Backpropagation Algorithm Software Open
This software is an implementation of the backpropagation algorithm for Intel's neuromorphic research processor, Loihi. The software implements the neural circuit itself and a demonstration application where the MNIST dataset (a standard t…
View article: The Backpropagation Algorithm Implemented on Spiking Neuromorphic Hardware
The Backpropagation Algorithm Implemented on Spiking Neuromorphic Hardware Open
The capabilities of natural neural systems have inspired new generations of machine learning algorithms as well as neuromorphic very large-scale integrated (VLSI) circuits capable of fast, low-power information processing. However, it has …
View article: Event-driven Vision and Control for UAVs on a Neuromorphic Chip
Event-driven Vision and Control for UAVs on a Neuromorphic Chip Open
Event-based vision sensors achieve up to three orders of magnitude better speed vs. power consumption trade off in high-speed control of UAVs compared to conventional image sensors. Event-based cameras produce a sparse stream of events tha…
View article: Event-based PID controller fully realized in neuromorphic hardware: a one DoF study
Event-based PID controller fully realized in neuromorphic hardware: a one DoF study Open
Spiking Neuronal Networks (SNNs) realized in neuromorphic hardware lead to low-power and low-latency neuronal computing architectures. Neuromorphic computing systems are most efficient when all of perception, decision making, and motor con…
View article: Visual Pattern Recognition with on On-Chip Learning: Towards a Fully Neuromorphic Approach
Visual Pattern Recognition with on On-Chip Learning: Towards a Fully Neuromorphic Approach Open
We present a spiking neural network (SNN) for visual pattern recognition with on-chip learning on neuromorphichardware. We show how this network can learn simple visual patterns composed of horizontal and vertical bars sensed by a Dynamic …
View article: Towards neuromorphic control: A spiking neural network based PID controller for UAV
Towards neuromorphic control: A spiking neural network based PID controller for UAV Open
In this work, we present a spiking neural network(SNN) based PID controller on a neuromorphic chip. On-chipSNNs are currently being explored in low-power AI applications.Due to potentially ultra-low power consumption, low latency,and high …
View article: An On-chip Spiking Neural Network for Estimation of the Head Pose of the iCub Robot
An On-chip Spiking Neural Network for Estimation of the Head Pose of the iCub Robot Open
In this work, we present a neuromorphic architecture for head pose estimation and scene representation for the humanoid iCub robot. The spiking neuronal network is fully realized in Intel's neuromorphic research chip, Loihi, and precisely …
View article: Event-Based Attention and Tracking on Neuromorphic Hardware
Event-Based Attention and Tracking on Neuromorphic Hardware Open
We present a fully event-driven vision and processing system for selective attention and tracking, realized on a neuromorphic processor Loihi interfaced to an event-based Dynamic Vision Sensor DAVIS. The attention mechanism is realized as …
View article: 2019 Theoretical Division Lightning Talk Series
2019 Theoretical Division Lightning Talk Series Open
All members of the Theoretical (T) Division Community, students, staff members, group leaders, division management and other interested individuals are invited to come and support the following student(s) during their Lightning Talk presen…
View article: Pose Estimation and Map Formation with Spiking Neural Networks: towards Neuromorphic SLAM
Pose Estimation and Map Formation with Spiking Neural Networks: towards Neuromorphic SLAM Open
In this paper, we investigate the use of ultra low-power, mixed signal analog/digital neuromorphic hardware for implementation of biologically inspired neuronal path integration and map formation for a mobile robot. We perform spiking netw…