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04/10/2023
Brain-Inspired Spiking Neural Network for Online Unsupervised Time Series Prediction
Energy and data-efficient online time series prediction for predicting e...
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02/22/2023
Unsupervised 3D Object Learning through Neuron Activity aware Plasticity
We present an unsupervised deep learning model for 3D object classificat...
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02/22/2023
Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles
This paper shows that the heterogeneity in neuronal and synaptic dynamic...
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10/28/2022
Forecasting local behavior of multi-agent system and its application to forest fire model
In this paper, we study a CNN-LSTM model to forecast the state of a spec...
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09/22/2022
Heterogeneous Recurrent Spiking Neural Network for Spatio-Temporal Classification
Spiking Neural Networks are often touted as brain-inspired learning mode...
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08/29/2022
An Algorithm-Hardware Co-design Framework to Overcome Imperfections of Mixed-signal DNN Accelerators
In recent years, processing in memory (PIM) based mixedsignal designs ha...
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08/19/2022
Forecasting Evolution of Clusters in StarCraft II with Hebbian Learning
Tactics in StarCraft II are closely related to group behavior of the gam...
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08/11/2022
Learning Point Processes using Recurrent Graph Network
We present a novel Recurrent Graph Network (RGN) approach for predicting...
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07/13/2022
Unsupervised Hebbian Learning on Point Sets in StarCraft II
Learning the evolution of real-time strategy (RTS) game is a challenging...
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06/24/2022
XMD: An Expansive Hardware-telemetry based Malware Detector to enhance Endpoint Detection
Hardware-based Malware Detectors (HMDs) have shown promise in detecting ...
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06/03/2022
Radar Guided Dynamic Visual Attention for Resource-Efficient RGB Object Detection
An autonomous system's perception engine must provide an accurate unders...
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04/30/2022
RADNet: A Deep Neural Network Model for Robust Perception in Moving Autonomous Systems
Interactive autonomous applications require robustness of the perception...
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03/16/2022
Unraveled Multilevel Transformation Networks for Predicting Sparsely-Observed Spatiotemporal Dynamics
In this paper, we address the problem of predicting complex, nonlinear s...
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07/24/2021
μDARTS: Model Uncertainty-Aware Differentiable Architecture Search
We present a Model Uncertainty-aware Differentiable ARchiTecture Search ...
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05/31/2021
Characterization of Generalizability of Spike Timing Dependent Plasticity trained Spiking Neural Networks
A Spiking Neural Network (SNN) is trained with Spike Timing Dependent Pl...
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05/25/2021
A Quantum Hopfield Associative Memory Implemented on an Actual Quantum Processor
In this work, we present a Quantum Hopfield Associative Memory (QHAM) an...
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04/21/2021
A Fully Spiking Hybrid Neural Network for Energy-Efficient Object Detection
This paper proposes a Fully Spiking Hybrid Neural Network (FSHNN) for en...
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03/21/2021
Towards Improving the Trustworthiness of Hardware based Malware Detector using Online Uncertainty Estimation
Hardware-based Malware Detectors (HMDs) using Machine Learning (ML) mode...
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11/30/2020
A Deep Learning-based Collocation Method for Modeling Unknown PDEs from Sparse Observation
Deep learning-based modeling of dynamical systems driven by partial diff...
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09/24/2020
Neural Identification for Control
We present a new method for learning control law that stabilizes an unkn...
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04/14/2020
PhICNet: Physics-Incorporated Convolutional Recurrent Neural Networks for Modeling Dynamical Systems
Dynamical systems involving partial differential equations (PDEs) and or...
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01/24/2020
MagNet: Discovering Multi-agent Interaction Dynamics using Neural Network
We present the MagNet, a multi-agent interaction network to discover gov...
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09/11/2019
Improving Robustness of ReRAM-based Spiking Neural Network Accelerator with Stochastic Spike-timing-dependent-plasticity
Spike-timing-dependent-plasticity (STDP) is an unsupervised learning alg...
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09/11/2019
ScieNet: Deep Learning with Spike-assisted Contextual Information Extraction
Deep neural networks (DNNs) provide high image classification accuracy, ...
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07/09/2019
Application Inference using Machine Learning based Side Channel Analysis
The proliferation of ubiquitous computing requires energy-efficient as w...
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04/29/2019
Mixture of Pre-processing Experts Model for Noise Robust Deep Learning on Resource Constrained Platforms
Deep learning on an edge device requires energy efficient operation due ...
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06/19/2018
HybridNet: Integrating Model-based and Data-driven Learning to Predict Evolution of Dynamical Systems
The robotic systems continuously interact with complex dynamical systems...
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03/16/2018
Memory Slices: A Modular Building Block for Scalable, Intelligent Memory Systems
While reduction in feature size makes computation cheaper in terms of la...
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02/25/2018
Blindsight: Blinding EM Side-Channel Leakage using Built-In Fully Integrated Inductive Voltage Regulator
Modern high-performance as well as power-constrained System-on-Chips (So...
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02/11/2018
Edge-Host Partitioning of Deep Neural Networks with Feature Space Encoding for Resource-Constrained Internet-of-Things Platforms
This paper introduces partitioning an inference task of a deep neural ne...
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10/12/2017
NeuroTrainer: An Intelligent Memory Module for Deep Learning Training
This paper presents, NeuroTrainer, an intelligent memory module with in-...
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08/08/2017
Cascade Adversarial Machine Learning Regularized with a Unified Embedding
Deep neural network classifiers are vulnerable to small input perturbati...
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06/08/2017
