76 citations · 272 across the 13 of their papers we have counts for
16 papers
NeuroAI and Beyond: Bridging Between Advances in Neuroscience and Artificial Intelligence
Anthony Zador, Jean-Marc Fellous, Terrence Sejnowski +28
Neuroscience and Artificial Intelligence (AI) have made impressive progress in recent years but remain only loosely interconnected. Based on a workshop convened by the National Sci…
Visual Odometry with Neuromorphic Resonator Networks
Alpha Renner, Lazar Supic, Andreea Danielescu +4
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…
Neuromorphic Visual Scene Understanding with Resonator Networks
Alpha Renner, Lazar Supic, Andreea Danielescu +5
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 maj…
What does it mean to represent? Mental representations as falsifiable memory patterns
Eloy Parra-Barrero, Yulia Sandamirskaya
Representation is a key notion in neuroscience and artificial intelligence (AI). However, a longstanding philosophical debate highlights that specifying what counts as representati…
Event-driven Vision and Control for UAVs on a Neuromorphic Chip
Antonio Vitale, Alpha Renner, Celine Nauer +2
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…
Visual Pattern Recognition with on On-chip Learning: towards a Fully Neuromorphic Approach
Sandro Baumgartner, Alpha Renner, Raphaela Kreiser +3
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 co…
A Real-Time Retinomorphic Simulator Using a Conductance-Based Discrete Neuronal Network
Jason K. Eshraghian, Seungbum Baek, Wesley Thio +3
We present an optimized conductance-based retina microcircuit simulator which transforms light stimuli into a series of graded and spiking action potentials through photo transduct…
Numerical and experimental realization of analytical SLAM
Jozef Bucko, Yulia Sandamirskaya, Jean-Jacques Slotine
Analytical approach to SLAM problem was introduced in the recent years. In our work we investigate the method numerically with the motivation of using the algorithm in a real hardw…
Parameter Optimization and Learning in a Spiking Neural Network for UAV Obstacle Avoidance targeting Neuromorphic Processors
Llewyn Salt, David Howard, Giacomo Indiveri +1
The Lobula Giant Movement Detector (LGMD) is an identified neuron of the locust that detects looming objects and triggers the insect's escape responses. Understanding the neural pr…
Event-based attention and tracking on neuromorphic hardware
Alpha Renner, Matthew Evanusa, Yulia Sandamirskaya
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 V…
Digital Multiplier-less Event-Driven Spiking Neural Network Architecture for Learning a Context-Dependent Task
Hajar Asgari, BabakMazloom-Nezhad Maybodi, Raphaela Kreiser +1
Neuromorphic engineers aim to develop event-based spiking neural networks (SNNs) in hardware. These SNNs closer resemble dynamics of biological neurons than todays' artificial neur…
Closing the Accuracy Gap in an Event-Based Visual Recognition Task
Bodo Rückauer, Nicolas Känzig, Shih-Chii Liu +2
Mobile and embedded applications require neural networks-based pattern recognition systems to perform well under a tight computational budget. In contrast to commonly used synchron…
The importance of space and time in neuromorphic cognitive agents
Giacomo Indiveri, Yulia Sandamirskaya
Artificial neural networks and computational neuroscience models have made tremendous progress, allowing computers to achieve impressive results in artificial intelligence (AI) app…
Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor
Sebastian Glatz, Julien N. P. Martel, Raphaela Kreiser +2
Neuromorphic computing is a new paradigm for design of both the computing hardware and algorithms inspired by biological neural networks. The event-based nature and the inherent pa…
Differential Evolution and Bayesian Optimisation for Hyper-Parameter Selection in Mixed-Signal Neuromorphic Circuits Applied to UAV Obstacle Avoidance
Llewyn Salt, David Howard, Giacomo Indiveri +1
The Lobula Giant Movement Detector (LGMD) is a an identified neuron of the locust that detects looming objects and triggers its escape responses. Understanding the neural principle…
Autonomous Reinforcement of Behavioral Sequences in Neural Dynamics
Sohrob Kazerounian, Matthew Luciw, Mathis Richter +1
We introduce a dynamic neural algorithm called Dynamic Neural (DN) SARSA(λ) for learning a behavioral sequence from delayed reward. DN-SARSA(λ) combines Dynamic Field Theory models…