Dhireesha Kudithipudi | DeepAI

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Featured Co-authors

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∙ 01/18/2023

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Despite the advancement of machine learning techniques in recent years, ...

9 Megan M. Baker, et al. ∙

∙ 04/06/2021

TENT: Efficient Quantization of Neural Networks on the tiny Edge with Tapered FixEd PoiNT

In this research, we propose a new low-precision framework, TENT, to lev...

0 Hamed F. Langroudi, et al. ∙

∙ 06/22/2020

End-to-End Memristive HTM System for Pattern Recognition and Sequence Prediction

Neuromorphic systems that learn and predict from streaming inputs hold s...

0 Abdullah M. Zyarah, et al. ∙

∙ 02/26/2020

Metaplasticity in Multistate Memristor Synaptic Networks

Recent studies have shown that metaplastic synapses can retain informati...

0 Fatima Tuz Zohora, et al. ∙

∙ 08/06/2019

Cheetah: Mixed Low-Precision Hardware Software Co-Design Framework for DNNs on the Edge

Low-precision DNNs have been extensively explored in order to reduce the...

10 Hamed F. Langroudi, et al. ∙

∙ 07/30/2019

Deep Learning Training on the Edge with Low-Precision Posits

Recently, the posit numerical format has shown promise for DNN data repr...

0 Hamed F. Langroudi, et al. ∙

∙ 07/01/2019

Analysis of Wide and Deep Echo State Networks for Multiscale Spatiotemporal Time Series Forecasting

Echo state networks are computationally lightweight reservoir models ins...

0 Zachariah Carmichael, et al. ∙

∙ 03/25/2019

Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks

Deep neural networks (DNNs) have been demonstrated as effective prognost...

0 Zachariah Carmichael, et al. ∙

∙ 12/27/2018

Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis

Hierarchical temporal memory (HTM) is a biomimetic sequence memory algor...

0 Abdullah M. Zyarah, et al. ∙

∙ 12/05/2018

Deep Positron: A Deep Neural Network Using the Posit Number System

The recent surge of interest in Deep Neural Networks (DNNs) has led to i...

0 Zachariah Carmichael, et al. ∙

∙ 08/17/2018

Neuromorphic Architecture for the Hierarchical Temporal Memory

A biomimetic machine intelligence algorithm, that holds promise in creat...

0 Abdullah M. Zyarah, et al. ∙

∙ 08/01/2018

Mod-DeepESN: Modular Deep Echo State Network

Neuro-inspired recurrent neural network algorithms, such as echo state n...

0 Zachariah Carmichael, et al. ∙

∙ 05/22/2018

Deep Learning Inference on Embedded Devices: Fixed-Point vs Posit

Performing the inference step of deep learning in resource constrained e...

0 Seyed H. F. Langroudi, et al. ∙

∙ 02/20/2018

On the Statistical Challenges of Echo State Networks and Some Potential Remedies

Echo state networks are powerful recurrent neural networks. However, the...

0 Qiuyi Wu, et al. ∙

∙ 11/03/2017

Convolutional Drift Networks for Video Classification

Analyzing spatio-temporal data like video is a challenging task that req...

0 Dillon Graham, et al. ∙

∙ 11/09/2016

Non-volatile Hierarchical Temporal Memory: Hardware for Spatial Pooling

Hierarchical Temporal Memory (HTM) is a biomimetic machine learning algo...

0 Lennard Streat, et al. ∙

∙ 01/27/2016

Unsupervised Learning in Neuromemristive Systems

Neuromemristive systems (NMSs) currently represent the most promising pl...

0 Cory Merkel, et al. ∙

∙ 01/22/2016

A Mathematical Formalization of Hierarchical Temporal Memory's Spatial Pooler

Hierarchical temporal memory (HTM) is an emerging machine learning algor...

0 James Mnatzaganian, et al. ∙