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2020 – today
- 2024
[i5]Nicholas Soures, Peter Helfer, Anurag Reddy Daram, Tej Pandit, Dhireesha Kudithipudi:
TACOS: Task Agnostic Continual Learning in Spiking Neural Networks. CoRR abs/2409.00021 (2024)- 2023
- [j2]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:
A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks 160: 274-296 (2023) - [c4]Anurag Reddy Daram, Dhireesha Kudithipudi:
NEO: Neuron State Dependent Mechanisms for Efficient Continual Learning. NICE 2023: 11-19 - [i4]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 Dimitri 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:
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR abs/2301.07799 (2023) - [i3]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:
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR abs/2304.04640 (2023) - [i2]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:
Design Principles for Lifelong Learning AI Accelerators. CoRR abs/2310.04467 (2023) - [i1]Ray A. O. Sinurat, Anurag Reddy Daram, Haryadi S. Gunawi, Robert B. Ross, Sandeep Madireddy:
Towards Continually Learning Application Performance Models. CoRR abs/2310.16996 (2023) - 2022
- [j1]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:
Biological underpinnings for lifelong learning machines. Nat. Mach. Intell. 4(3): 196-210 (2022) - 2021
- [c3]Fatima Tuz Zohora, Vedant Karia, Anurag Reddy Daram, Abdullah M. Zyarah, Dhireesha Kudithipudi:
MetaplasticNet: Architecture with Probabilistic Metaplastic Synapses for Continual Learning. ISCAS 2021: 1-5
2010 – 2019
- 2019
- [c2]Anurag Reddy Daram, Dhireesha Kudithipudi, Angel Yanguas-Gil:
Task-Based Neuromodulation Architecture for Lifelong Learning. ISQED 2019: 191-197 - 2018
- [c1]Anurag Reddy Daram, Karan Paluru, Vedant Karia, Dhireesha Kudithipudi:
Scalable IP Core for Feed Forward Random Networks. ELM 2018: 253-262
Coauthor Index
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