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07/21/2023
Neuromorphic Online Learning for Spatiotemporal Patterns with a Forward-only Timeline
Spiking neural networks (SNNs) are bio-plausible computing models with h...
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05/08/2021
In-Hardware Learning of Multilayer Spiking Neural Networks on a Neuromorphic Processor
Although widely used in machine learning, backpropagation cannot directl...
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04/21/2021
Neuromorphic Algorithm-hardware Codesign for Temporal Pattern Learning
Neuromorphic computing and spiking neural networks (SNN) mimic the behav...
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07/07/2020
Multivariate Time Series Classification Using Spiking Neural Networks
There is an increasing demand to process streams of temporal data in ene...
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06/06/2020
MAGNet: Multi-Region Attention-Assisted Grounding of Natural Language Queries at Phrase Level
Grounding free-form textual queries necessitates an understanding of the...
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03/22/2020
GISNet: Graph-Based Information Sharing Network For Vehicle Trajectory Prediction
The trajectory prediction is a critical and challenging problem in the d...
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03/22/2020
Mission-Aware Spatio-Temporal Deep Learning Model for UAS Instantaneous Density Prediction
The number of daily sUAS operations in uncontrolled low altitude airspac...
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02/27/2020
Simulation of Real-time Routing for UAS traffic Management with Communication and Airspace Safety Considerations
Small Unmanned Aircraft Systems (sUAS) will be an important component of...
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02/19/2020
Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network
The recent discovered spatial-temporal information processing capability...
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01/11/2020
Embedding Compression with Isotropic Iterative Quantization
Continuous representation of words is a standard component in deep learn...
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01/08/2020
High-Level Plan for Behavioral Robot Navigation with Natural Language Directions and R-NET
When the navigational environment is known, it can be represented as a g...
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02/28/2019
CircConv: A Structured Convolution with Low Complexity
Deep neural networks (DNNs), especially deep convolutional neural networ...
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12/12/2018
E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs
Recurrent Neural Networks (RNNs) are becoming increasingly important for...
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05/10/2018
Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing
Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendo...
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04/11/2018
Learning Topics using Semantic Locality
The topic modeling discovers the latent topic probability of the given t...
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03/20/2018
Efficient Recurrent Neural Networks using Structured Matrices in FPGAs
Recurrent Neural Networks (RNNs) are becoming increasingly important for...
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03/20/2018
C3PO: Database and Benchmark for Early-stage Malicious Activity Detection in 3D Printing
Increasing malicious users have sought practices to leverage 3D printing...
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03/14/2018
C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs
Recently, significant accuracy improvement has been achieved for acousti...
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02/18/2018
Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework
Hardware accelerations of deep learning systems have been extensively in...
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08/29/2017
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices
Large-scale deep neural networks (DNNs) are both compute and memory inte...
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03/12/2017
Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks
Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecede...
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11/18/2016
