Search Results for author: Nicholas Soures

Found 5 papers, 1 papers with code

Metaplasticity in Multistate Memristor Synaptic Networks

no code implementations26 Feb 2020 Fatima Tuz Zohora, Abdullah M. Zyarah, Nicholas Soures, Dhireesha Kudithipudi

In the $128\times128$ network, it is observed that the number of input patterns the multistate synapse can classify is $\simeq$ 2. 1x that of a simple binary synapse model, at a mean accuracy of $\geq$ 75% .

Continual Learning

SIRNet: Understanding Social Distancing Measures with Hybrid Neural Network Model for COVID-19 Infectious Spread

2 code implementations22 Apr 2020 Nicholas Soures, David Chambers, Zachariah Carmichael, Anurag Daram, Dimpy P. Shah, Kal Clark, Lloyd Potter, Dhireesha Kudithipudi

The SARS-CoV-2 infectious outbreak has rapidly spread across the globe and precipitated varying policies to effectuate physical distancing to ameliorate its impact.

Populations and Evolution

Design Principles for Lifelong Learning AI Accelerators

no code implementations5 Oct 2023 Dhireesha Kudithipudi, Anurag Daram, Abdullah M. Zyarah, Fatima Tuz Zohora, James B. Aimone, Angel Yanguas-Gil, Nicholas Soures, Emre Neftci, Matthew Mattina, Vincenzo Lomonaco, Clare D. Thiem, Benjamin Epstein

Lifelong learning - an agent's ability to learn throughout its lifetime - is a hallmark of biological learning systems and a central challenge for artificial intelligence (AI).

Continual Learning and Catastrophic Forgetting

no code implementations8 Mar 2024 Gido M. van de Ven, Nicholas Soures, Dhireesha Kudithipudi

This book chapter delves into the dynamics of continual learning, which is the process of incrementally learning from a non-stationary stream of data.

Continual Learning

Probabilistic Metaplasticity for Continual Learning with Memristors

no code implementations13 Mar 2024 Fatima Tuz Zohora, Vedant Karia, Nicholas Soures, Dhireesha Kudithipudi

The proposed mechanism eliminates high-precision modification to weight magnitude and consequently, high-precision memory for gradient accumulation.

Continual Learning

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