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ORCIDAmeya D. Patil
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2020 – today
- 2024
[d1]Ghazal Kaviani, Yavuz Yarici, Mohit Prabhushankar, Ghassan AlRegib, Mashhour Solh, Ameya Patil:
DARai: Daily Activity Recordings for AI and ML aplications. IEEE DataPort, 2024
- [i8]Niki Nezakati, Md Kaykobad Reza, Ameya Patil, Mashhour Solh, M. Salman Asif:
MMP: Towards Robust Multi-Modal Learning with Masked Modality Projection. CoRR abs/2410.03010 (2024) - [i7]Ziwei Dong, Ameya Patil, Yuichi Shoda, Leilani Battle, Emily Wall:
Behavior Matters: An Alternative Perspective on Promoting Responsible Data Science. CoRR abs/2410.17273 (2024) - 2023
- [j6]Leilani Battle, Ameya Patil, Trevor A. Branch, Zoe Rand:
Visualizing Historical Whaling Voyages over Time. Interactions 30(5): 22-23 (2023) - [j5]Ameya Patil, Gaëlle Richer
, Christopher Jermaine, Dominik Moritz, Jean-Daniel Fekete:
Studying Early Decision Making with Progressive Bar Charts. IEEE Trans. Vis. Comput. Graph. 29(1): 407-417 (2023) - [c9]Ameya Patil, Zoe Rand, Trevor Branch, Leilani Battle:
WhaleVis: Visualizing the History of Commercial Whaling. IEEE VIS (Short Papers) 2023: 96-100 - [i6]Ameya Patil, Zoe Rand, Trevor Branch, Leilani Battle:
WhaleVis: Visualizing the History of Commercial Whaling. CoRR abs/2308.04552 (2023) - 2022
- [c8]Saion K. Roy, Ameya Patil, Naresh R. Shanbhag:
Fundamental Limits on the Computational Accuracy of Resistive Crossbar-based In-memory Architectures. ISCAS 2022: 384-388 - 2021
- [i5]Ameya D. Patil, Michael Tuttle, Alexander G. Schwing, Naresh R. Shanbhag:
Robustifying 𝓁∞ Adversarial Training to the Union of Perturbation Models. CoRR abs/2105.14710 (2021) - 2020
- [j4]Mingu Kang, Yongjune Kim, Ameya D. Patil, Naresh R. Shanbhag:
Deep In-Memory Architectures for Machine Learning-Accuracy Versus Efficiency Trade-Offs. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. 67-I(5): 1627-1639 (2020) - [c7]Sujan K. Gonugondla, Ameya D. Patil, Naresh R. Shanbhag:
SWIPE: Enhancing Robustness of ReRAM Crossbars for In-memory Computing. ICCAD 2020: 93:1-93:9
2010 – 2019
- 2019
- [j3]Naresh R. Shanbhag, Naveen Verma, Yongjune Kim, Ameya D. Patil, Lav R. Varshney:
Shannon-Inspired Statistical Computing for the Nanoscale Era. Proc. IEEE 107(1): 90-107 (2019) - [c6]Ameya D. Patil, Haocheng Hua, Sujan K. Gonugondla, Mingu Kang, Naresh R. Shanbhag:
An MRAM-Based Deep In-Memory Architecture for Deep Neural Networks. ISCAS 2019: 1-5 - [c5]Ameya D. Patil, Sasikanth Manipatruni, Dmitri E. Nikonov, Ian A. Young, Naresh R. Shanbhag:
An Energy-Efficient Classifier via Boosted Spin Channel Networks. ISCAS 2019: 1-5 - [i4]Angeline Aguinaldo, Ping-Yeh Chiang, Alexander Gain, Ameya Patil, Kolten Pearson, Soheil Feizi:
Compressing GANs using Knowledge Distillation. CoRR abs/1902.00159 (2019) - 2018
- [j2]Mingu Kang, Sujan K. Gonugondla, Ameya Patil, Naresh R. Shanbhag:
A Multi-Functional In-Memory Inference Processor Using a Standard 6T SRAM Array. IEEE J. Solid State Circuits 53(2): 642-655 (2018) - 2017
- [c4]Ameya Patil, Naresh R. Shanbhag, Lav R. Varshney, Eric Pop, H.-S. Philip Wong, Subhasish Mitra, Jan M. Rabaey, Jeffrey A. Weldon, Larry T. Pileggi, Sasikanth Manipatruni, Dmitri E. Nikonov, Ian A. Young:
A Systems Approach to Computing in Beyond CMOS Fabrics: Invited. DAC 2017: 18:1-18:2 - [c3]Charbel Sakr, Ameya D. Patil, Sai Zhang, Yongjune Kim, Naresh R. Shanbhag:
Minimum precision requirements for the SVM-SGD learning algorithm. ICASSP 2017: 1138-1142 - [i3]Ameya D. Patil, Sasikanth Manipatruni, Dmitri E. Nikonov, Ian A. Young, Naresh R. Shanbhag:
Shannon-inspired Statistical Computing to Enable Spintronics. CoRR abs/1702.06119 (2017) - 2016
- [j1]Vineet Sunil Gattani, Kiran Kumar Vupparaboina, Ameya Patil, Jay Chhablani, Ashutosh Richhariya, Soumya Jana:
Semi-automated quantification of retinal IS/OS damage in en-face OCT image. Comput. Biol. Medicine 69: 52-60 (2016) - [c2]Jungwook Choi, Ameya D. Patil, Rob A. Rutenbar, Naresh R. Shanbhag:
Analysis of error resiliency of belief propagation in computer vision. ICASSP 2016: 1060-1064 - [i2]Charbel Sakr, Ameya Patil, Sai Zhang, Naresh R. Shanbhag:
Understanding the Energy and Precision Requirements for Online Learning. CoRR abs/1607.00669 (2016) - [i1]Mingu Kang, Sujan K. Gonugondla, Ameya Patil, Naresh R. Shanbhag:
A 481pJ/decision 3.4M decision/s Multifunctional Deep In-memory Inference Processor using Standard 6T SRAM Array. CoRR abs/1610.07501 (2016) - 2014
- [c1]Srinath Nizampatnam, Ameya D. Patil, Kiran Kumar Vupparaboina, Soumya Jana, Jay Chhablani, Ashutosh Richhariya:
Automated detection of choroid boundary and vessels in optical coherence tomography images. EMBC 2014: 166-169
Coauthor Index
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