Digital neuromorphic design of a Liquid State Machine for real-time processing. - Anvesh Polepalli; Nicholas Soures; Dhireesha Kudithipudi (ICRC, 2016)

Neuromemristive Systems: Boosting Efficiency through Brain-Inspired Computing. - Cory E. Merkel; Raqibul Hasan; Nicholas Soures; Dhireesha Kudithipudi; Tarek M. Taha; Sapan Agarwal; Matthew J. Marinella (Computer, 2016)

Robustness of a memristor based liquid state machine. - Nicholas Soures; Lydia Hays; Dhireesha Kudithipudi (IJCNN, 2017)

Ziksa: On-chip learning accelerator with memristor crossbars for multilevel neural networks. - Abdullah M. Zyarah; Nicholas Soures; Lydia Hays; Robin Jacobs-Gedrim; Sapan Agarwal; Matthew J. Marinella; Dhireesha Kudithipudi (ISCAS, 2017)

On-device STDP and synaptic normalization for neuromemristive spiking neural network. - Nicholas Soures; Lydia Hays; Eric Bohannon; Abdullah M. Zyarah; Dhireesha Kudithipudi (MWSCAS, 2017)

Reservoir Computing in Embedded Systems: Three variants of the reservoir algorithm. - Nicholas Soures; Corey Merkel; Dhireesha Kudithipudi; Clare Thiem; Nathan R. McDonald (IEEE Consumer Electron. Mag., 2017)

On-Device Learning in Memristor Spiking Neural Networks. - Abdullah M. Zyarah; Nicholas Soures; Dhireesha Kudithipudi (ISCAS, 2018)

Spiking Reservoir Networks: Brain-inspired recurrent algorithms that use random, fixed synaptic strengths. - Nicholas Soures; Dhireesha Kudithipudi (IEEE Signal Process. Mag., 2019)

Metaplasticity in Multistate Memristor Synaptic Networks. - Fatima Tuz Zohora; Abdullah M. Zyarah; Nicholas Soures; Dhireesha Kudithipudi (ISCAS, 2020)

SCOLAR: A Spiking Digital Accelerator with Dual Fixed Point for Continual Learning. - Vedant Karia; Fatima Tuz Zohora; Nicholas Soures; Dhireesha Kudithipudi (ISCAS, 2022)

Biological underpinnings for lifelong learning machines. - Dhireesha Kudithipudi; Mario Aguilar-Simon; Jonathan Babb; Maxim Bazhenov; Douglas Blackiston; Josh C. Bongard; Andrew P. Brna; Suraj Chakravarthi Raja; Nick Cheney; Jeff Clune; Anurag Reddy Daram; Stefano Fusi; et al. (Nat. Mach. Intell., 2022)

Design Principles for Lifelong Learning AI Accelerators. - Dhireesha Kudithipudi; Anurag Reddy 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 R. Epstein (CoRR, 2023)

Advancing Neuro-Inspired Lifelong Learning for Edge with Co-Design. - Nicholas Soures; Vedant Karia; Dhireesha Kudithipudi (AAAI Spring Symposia, 2024)

Continual Learning and Catastrophic Forgetting. - Gido M. van de Ven; Nicholas Soures; Dhireesha Kudithipudi (CoRR, 2024)

Probabilistic Metaplasticity for Continual Learning with Memristors. - Fatima Tuz Zohora; Vedant Karia; Nicholas Soures; Dhireesha Kudithipudi (CoRR, 2024)

TACOS: Task Agnostic Continual Learning in Spiking Neural Networks. - Nicholas Soures; Peter Helfer; Anurag Reddy Daram; Tej Pandit; Dhireesha Kudithipudi (CoRR, 2024)

Learning Continually in Silicon. - Nicholas Soures; Jayanta Dey; Dhireesha Kudithipudi (Computer, 2024)

Temporal Chunking Enhances Recognition of Implicit Sequential Patterns. - Jayanta Dey; Nicholas Soures; Miranda Gonzales; Itamar Lerner; Christopher Kanan; Dhireesha Kudithipudi (CoRR, 2025)