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08/29/2022
Bayesian Continual Learning via Spiking Neural Networks
Among the main features of biological intelligence are energy efficiency...
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12/03/2021
Learning to Broadcast for Ultra-Reliable Communication with Differential Quality of Service via the Conditional Value at Risk
Broadcast/multicast communication systems are typically designed to opti...
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06/02/2021
Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck
One of the key challenges in training Spiking Neural Networks (SNNs) is ...
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02/05/2021
Multi-Sample Online Learning for Spiking Neural Networks based on Generalized Expectation Maximization
Spiking Neural Networks (SNNs) offer a novel computational paradigm that...
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12/15/2020
BiSNN: Training Spiking Neural Networks with Binary Weights via Bayesian Learning
Artificial Neural Network (ANN)-based inference on battery-powered devic...
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10/27/2020
Spiking Neural Networks – Part III: Neuromorphic Communications
Synergies between wireless communications and artificial intelligence ar...
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10/27/2020
Spiking Neural Networks – Part II: Detecting Spatio-Temporal Patterns
Inspired by the operation of biological brains, Spiking Neural Networks ...
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10/27/2020
Spiking Neural Networks – Part I: Detecting Spatial Patterns
Spiking Neural Networks (SNNs) are biologically inspired machine learnin...
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09/03/2020
End-to-End Learning of Neuromorphic Wireless Systems for Low-Power Edge Artificial Intelligence
This paper introduces a novel "all-spike" low-power solution for remote ...
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07/23/2020
Multi-Compartment Variational Online Learning for Spiking Neural Networks
Spiking Neural Networks (SNNs) offer a novel computational paradigm that...
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04/20/2020
VOWEL: A Local Online Learning Rule for Recurrent Networks of Probabilistic Spiking Winner-Take-All Circuits
Networks of spiking neurons and Winner-Take-All spiking circuits (WTA-SN...
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10/21/2019
Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence
Spiking Neural Networks (SNNs) offer a promising alternative to conventi...
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10/02/2019
An Introduction to Probabilistic Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications
Spiking neural networks (SNNs) are distributed trainable systems whose c...
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10/02/2019
An Introduction to Probabilistic Spiking Neural Networks
Spiking neural networks (SNNs) are distributed trainable systems whose c...
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09/09/2019
Solving Continual Combinatorial Selection via Deep Reinforcement Learning
We consider the Markov Decision Process (MDP) of selecting a subset of i...
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08/23/2019
Learning to Demodulate from Few Pilots via Offline and Online Meta-Learning
This paper considers an Internet-of-Things (IoT) scenario in which devic...
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03/06/2019
Learning How to Demodulate from Few Pilots via Meta-Learning
Consider an Internet-of-Things (IoT) scenario in which devices transmit ...
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12/10/2018
Spiking Neural Networks: A Stochastic Signal Processing Perspective
Spiking Neural Networks (SNNs) are distributed systems whose computing e...
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10/21/2018
Training Dynamic Exponential Family Models with Causal and Lateral Dependencies for Generalized Neuromorphic Computing
Neuromorphic hardware platforms, such as Intel's Loihi chip, support the...
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09/13/2018
Simulation-based Distributed Coordination Maximization over Networks
In various online/offline multi-agent networked environments, it is very...
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04/29/2018
Learning Data Dependency with Communication Cost
In this paper, we consider the problem of recovering a graph that repres...
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05/26/2016