Anurag Reddy Daram

According to our database, Anurag Reddy Daram authored at least 10 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

TACOS: Task Agnostic Continual Learning in Spiking Neural Networks.

Nicholas Soures, Peter Helfer, Anurag Reddy Daram, Tej Pandit, Dhireesha Kudithipudi

CoRR, 2024

2023

A domain-agnostic approach for characterization of lifelong learning systems.

Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha

Neural Networks, March, 2023

Towards Continually Learning Application Performance Models.

Ray A. O. Sinurat, Anurag Reddy Daram, Haryadi S. Gunawi, Robert B. Ross, Sandeep Madireddy

CoRR, 2023

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

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking.

Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Michael Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi

CoRR, 2023

NEO: Neuron State Dependent Mechanisms for Efficient Continual Learning.

Anurag Reddy Daram, Dhireesha Kudithipudi

Proceedings of the Neuro-Inspired Computational Elements Conference, 2023

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, Peter Helfer, Leslie Kay, Nicholas Ketz, Zsolt Kira, Soheil Kolouri, Jeffrey L. Krichmar, Sam Kriegman, Michael Levin, Sandeep Madireddy, Santosh Manicka, Ali Marjaninejad, Bruce McNaughton, Risto Miikkulainen, Zaneta Navratilova, Tej Pandit, Alice Parker, Praveen K. Pilly, Sebastian Risi, Terrence J. Sejnowski, Andrea Soltoggio, Nicholas Soures, Andreas S. Tolias, Darío Urbina-Meléndez, Francisco J. Valero Cuevas, Gido M. van de Ven, Joshua T. Vogelstein, Felix Wang, Ron Weiss, Angel Yanguas-Gil, Xinyun Zou, Hava T. Siegelmann

Nat. Mach. Intell., 2022

2021

MetaplasticNet: Architecture with Probabilistic Metaplastic Synapses for Continual Learning.

Fatima Tuz Zohora, Vedant Karia, Anurag Reddy Daram, Abdullah M. Zyarah, Dhireesha Kudithipudi

Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

2019

Task-Based Neuromodulation Architecture for Lifelong Learning.

Anurag Reddy Daram, Dhireesha Kudithipudi, Angel Yanguas-Gil

Proceedings of the 20th International Symposium on Quality Electronic Design, 2019

2018

Scalable IP Core for Feed Forward Random Networks.

Anurag Reddy Daram, Karan Paluru, Vedant Karia, Dhireesha Kudithipudi

Proceedings of ELM 2018, 2018