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2020 – today
- 2024
[c44]Zihang Song, Prabodh Katti, Osvaldo Simeone, Bipin Rajendran:
Stochastic Spiking Attention: Accelerating Attention with Stochastic Computing in Spiking Networks. AICAS 2024: 31-35- [c43]Amit Singh, Payam Barnaghi, Geoff V. Merrett, Eiman Kanjo, Rishad A. Shafik, Aurora Gil de Castro, Florenc Demrozi, Federica Zonzini, Amna Anwar, Bipin Rajendran, Osvaldo Simeone:
Welcome Message from the Chairs. COINS 2024: 1 - [c42]Prabodh Katti, Anagha Nimbekar, Chen Li, Amit Acharyya, Bashir M. Al-Hashimi, Bipin Rajendran:
Bayesian Inference Accelerator for Spiking Neural Networks. ISCAS 2024: 1-5 - [c41]Zihang Song, Osvaldo Simeone, Bipin Rajendran:
Neuromorphic In-Context Learning for Energy-Efficient MIMO Symbol Detection. SPAWC 2024: 1-5 - [i30]Prabodh Katti, Anagha Nimbekar, Chen Li, Amit Acharyya, Bashir M. Al-Hashimi, Bipin Rajendran:
Bayesian Inference Accelerator for Spiking Neural Networks. CoRR abs/2401.15453 (2024) - [i29]Zihang Song, Prabodh Katti, Osvaldo Simeone, Bipin Rajendran:
Stochastic Spiking Attention: Accelerating Attention with Stochastic Computing in Spiking Networks. CoRR abs/2402.09109 (2024) - [i28]Robert O. Shea, Prabodh Katti, Bipin Rajendran:
Baseline Drift Tolerant Signal Encoding for ECG Classification with Deep Learning. CoRR abs/2405.00724 (2024) - [i27]Zihang Song, Prabodh Katti, Osvaldo Simeone, Bipin Rajendran:
Xpikeformer: Hybrid Analog-Digital Hardware Acceleration for Spiking Transformers. CoRR abs/2408.08794 (2024) - 2023
- [c40]Yiming Ai, Bipin Rajendran:
A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfaces. AICAS 2023: 1-5 - [c39]Prabodh Katti, Nicolas Skatchkovsky, Osvaldo Simeone, Bipin Rajendran, Bashir M. Al-Hashimi:
Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity. ISCAS 2023: 1-5 - [i26]Prabodh Katti, Nicolas Skatchkovsky, Osvaldo Simeone, Bipin Rajendran, Bashir M. Al-Hashimi:
Bayesian Inference on Binary Spiking Networks Leveraging Nanoscale Device Stochasticity. CoRR abs/2302.01302 (2023) - [i25]Yiming Ai, Bipin Rajendran:
A Convolutional Spiking Network for Gesture Recognition in Brain-Computer Interfaces. CoRR abs/2304.11106 (2023) - [i24]Flor Ortiz, Nicolas Skatchkovsky, Eva Lagunas, Wallace A. Martins, Geoffrey Eappen, Saed Daoud, Osvaldo Simeone, Bipin Rajendran, Symeon Chatzinotas:
Energy-Efficient On-Board Radio Resource Management for Satellite Communications via Neuromorphic Computing. CoRR abs/2308.11152 (2023) - [i23]Bipin Rajendran, Osvaldo Simeone, Bashir M. Al-Hashimi:
Towards Efficient and Trustworthy AI Through Hardware-Algorithm-Communication Co-Design. CoRR abs/2309.15942 (2023) - [i22]Chen Li, Bipin Rajendran:
Noise Adaptor in Spiking Neural Networks. CoRR abs/2312.05290 (2023) - 2022
- [j10]Bleema Rosenfeld
, Osvaldo Simeone, Bipin Rajendran:
Spiking Generative Adversarial Networks With a Neural Network Discriminator: Local Training, Bayesian Models, and Continual Meta-Learning. IEEE Trans. Computers 71(11): 2778-2791 (2022) - 2021
- [c38]Vinay Joshi, Wangxin He, Jae-sun Seo, Bipin Rajendran:
Hybrid In-Memory Computing Architecture for the Training of Deep Neural Networks. ISCAS 2021: 1-5 - [i21]Vinay Joshi, Wangxin He, Jae-sun Seo, Bipin Rajendran:
Hybrid In-memory Computing Architecture for the Training of Deep Neural Networks. CoRR abs/2102.05271 (2021) - [i20]Bleema Rosenfeld, Bipin Rajendran, Osvaldo Simeone:
Fast On-Device Adaptation for Spiking Neural Networks via Online-Within-Online Meta-Learning. CoRR abs/2103.03901 (2021) - [i19]Bleema Rosenfeld, Osvaldo Simeone, Bipin Rajendran:
Spiking Generative Adversarial Networks With a Neural Network Discriminator: Local Training, Bayesian Models, and Continual Meta-Learning. CoRR abs/2111.01750 (2021) - 2020
- [j9]Adnan Mehonic, Abu Sebastian, Bipin Rajendran, Osvaldo Simeone, Eleni Vasilaki, Anthony J. Kenyon:
Memristors - From In-Memory Computing, Deep Learning Acceleration, and Spiking Neural Networks to the Future of Neuromorphic and Bio-Inspired Computing. Adv. Intell. Syst. 2(11): 2000085 (2020) - [j8]Navin Anwani, Bipin Rajendran:
Training multi-layer spiking neural networks using NormAD based spatio-temporal error backpropagation. Neurocomputing 380: 67-77 (2020) - [c37]Shruti R. Kulkarni, Shihui Yin, Jae-sun Seo, Bipin Rajendran:
An On-Chip Learning Accelerator for Spiking Neural Networks using STT-RAM Crossbar Arrays. DATE 2020: 1019-1024 - [c36]Vinay Joshi, Geethan Karunaratne, Manuel Le Gallo, Irem Boybat, Christophe Piveteau, Abu Sebastian, Bipin Rajendran, Evangelos Eleftheriou:
ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning. ISCAS 2020: 1-5 - [i18]S. R. Nandakumar, Bipin Rajendran:
Bio-mimetic Synaptic Plasticity and Learning in a sub-500mV Cu/SiO2/W Memristor. CoRR abs/2001.09299 (2020) - [i17]S. R. Nandakumar, Manuel Le Gallo, Christophe Piveteau, Vinay Joshi, Giovanni Mariani, Irem Boybat, Geethan Karunaratne, Riduan Khaddam-Aljameh, Urs Egger, Anastasios Petropoulos, Theodore Antonakopoulos, Bipin Rajendran, Abu Sebastian, Evangelos Eleftheriou:
Mixed-precision deep learning based on computational memory. CoRR abs/2001.11773 (2020) - [i16]Vinay Joshi, Geethan Karunaratne, Manuel Le Gallo, Irem Boybat, Christophe Piveteau, Abu Sebastian, Bipin Rajendran, Evangelos Eleftheriou:
ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning. CoRR abs/2003.11256 (2020) - [i15]Adnan Mehonic, Abu Sebastian, Bipin Rajendran, Osvaldo Simeone, Eleni Vasilaki, Anthony J. Kenyon:
Memristors - from In-memory computing, Deep Learning Acceleration, Spiking Neural Networks, to the Future of Neuromorphic and Bio-inspired Computing. CoRR abs/2004.14942 (2020) - [i14]Anakha V. Babu, Osvaldo Simeone, Bipin Rajendran:
SpinAPS: A High-Performance Spintronic Accelerator for Probabilistic Spiking Neural Networks. CoRR abs/2008.02189 (2020)
2010 – 2019
- 2019
- [j7]Osvaldo Simeone, Bipin Rajendran, André Grüning, Evangelos Eleftheriou, Mike Davies, Sophie Denève, Guang-Bin Huang:
Learning Algorithms and Signal Processing for Brain-Inspired Computing [From the Guest Editors]. IEEE Signal Process. Mag. 36(6): 12-15 (2019) - [j6]Bipin Rajendran, Abu Sebastian, Michael Schmuker, Narayan Srinivasa, Evangelos Eleftheriou:
Low-Power Neuromorphic Hardware for Signal Processing Applications: A review of architectural and system-level design approaches. IEEE Signal Process. Mag. 36(6): 97-110 (2019) - [c35]Shruti R. Kulkarni, Deepak Vinayak Kadetotad, Shihui Yin, Jae-Sun Seo, Bipin Rajendran:
Neuromorphic Hardware Accelerator for SNN Inference based on STT-RAM Crossbar Arrays. ICECS 2019: 438-441 - [c34]S. R. Nandakumar, Irem Boybat, Vinay Joshi, Christophe Piveteau, Manuel Le Gallo, Bipin Rajendran, Abu Sebastian, Evangelos Eleftheriou:
Phase-Change Memory Models for Deep Learning Training and Inference. ICECS 2019: 727-730 - [c33]Bleema Rosenfeld, Osvaldo Simeone, Bipin Rajendran:
Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients. SPAWC 2019: 1-5 - [c32]Abu Sebastian, Irem Boybat, Martino Dazzi, Iason Giannopoulos, Vara Prasad Jonnalagadda, Vinay Joshi, Geethan Karunaratne, Benedikt Kersting, Riduan Khaddam-Aljameh, S. R. Nandakumar, Anastasios Petropoulos, Christophe Piveteau, Theodore Antonakopoulos, Bipin Rajendran, Manuel Le Gallo, Evangelos Eleftheriou:
Computational memory-based inference and training of deep neural networks. VLSI Circuits 2019: 168- - [i13]Bipin Rajendran, Abu Sebastian, Michael Schmuker, Narayan Srinivasa, Evangelos Eleftheriou:
Low-Power Neuromorphic Hardware for Signal Processing Applications. CoRR abs/1901.03690 (2019) - [i12]S. R. Nandakumar, Irem Boybat, Manuel Le Gallo, Evangelos Eleftheriou, Abu Sebastian, Bipin Rajendran:
Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses. CoRR abs/1905.11929 (2019) - [i11]Vinay Joshi, Manuel Le Gallo, Irem Boybat, Simon Haefeli, Christophe Piveteau, Martino Dazzi, Bipin Rajendran, Abu Sebastian, Evangelos Eleftheriou:
Accurate deep neural network inference using computational phase-change memory. CoRR abs/1906.03138 (2019) - 2018
- [j5]Anakha V. Babu, Sandip Lashkare, Udayan Ganguly, Bipin Rajendran:
Stochastic learning in deep neural networks based on nanoscale PCMO device characteristics. Neurocomputing 321: 227-236 (2018) - [j4]Shruti R. Kulkarni, Bipin Rajendran:
Spiking neural networks for handwritten digit recognition - Supervised learning and network optimization. Neural Networks 103: 118-127 (2018) - [c31]Shruti R. Kulkarni, Anakha V. Babu, Bipin Rajendran:
Acceleration of Convolutional Networks Using Nanoscale Memristive Devices. EANN 2018: 240-251 - [c30]Alireza Bagheri, Osvaldo Simeone, Bipin Rajendran:
Training Probabilistic Spiking Neural Networks with First- To-Spike Decoding. ICASSP 2018: 2986-2990 - [c29]Shruti R. Kulkarni, John M. Alexiades, Bipin Rajendran:
Live Demonstration: Image Classification Using Bio-inspired Spiking Neural Networks. ISCAS 2018: 1- - [c28]S. R. Nandakumar, Manuel Le Gallo, Irem Boybat, Bipin Rajendran, Abu Sebastian, Evangelos Eleftheriou:
Mixed-precision architecture based on computational memory for training deep neural networks. ISCAS 2018: 1-5 - [c27]Irem Boybat, S. R. Nandakumar, Manuel Le Gallo, Bipin Rajendran, Yusuf Leblebici, Abu Sebastian, Evangelos Eleftheriou:
Impact of conductance drift on multi-PCM synaptic architectures. NVMTS 2018: 1-4 - [c26]Alireza Bagheri, Osvaldo Simeone, Bipin Rajendran:
Adversarial Training for Probabilistic Spiking Neural Networks. SPAWC 2018: 1-5 - [i10]Alireza Bagheri, Osvaldo Simeone, Bipin Rajendran:
Adversarial Training for Probabilistic Spiking Neural Networks. CoRR abs/1802.08567 (2018) - [i9]Bleema Rosenfeld, Osvaldo Simeone, Bipin Rajendran:
Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients. CoRR abs/1810.09977 (2018) - [i8]Navin Anwani, Bipin Rajendran:
Training Multilayer Spiking Neural Networks using NormAD based Spatio-Temporal Error Backpropagation. CoRR abs/1811.10678 (2018) - 2017
- [c25]Shruti R. Kulkarni, John M. Alexiades, Bipin Rajendran:
Learning and real-time classification of hand-written digits with spiking neural networks. ICECS 2017: 128-131 - [c24]Anakha V. Babu, Bipin Rajendran:
Stochastic deep learning in memristive networks. ICECS 2017: 214-217 - [c23]Shruti R. Kulkarni, Anakha V. Babu, Bipin Rajendran:
Spiking neural networks - Algorithms, hardware implementations and applications. MWSCAS 2017: 426-431 - [c22]Irem Boybat, Manuel Le Gallo, S. R. Nandakumar, Timoleon Moraitis, Tomas Tuma, Bipin Rajendran, Yusuf Leblebici, Abu Sebastian, Evangelos Eleftheriou:
An efficient synaptic architecture for artificial neural networks. NVMTS 2017: 1-4 - [i7]Alireza Bagheri, Osvaldo Simeone, Bipin Rajendran:
Training Probabilistic Spiking Neural Networks with First-to-spike Decoding. CoRR abs/1710.10704 (2017) - [i6]Shruti R. Kulkarni, John M. Alexiades, Bipin Rajendran:
Learning and Real-time Classification of Hand-written Digits With Spiking Neural Networks. CoRR abs/1711.03637 (2017) - [i5]Anakha V. Babu, Bipin Rajendran:
Stochastic Deep Learning in Memristive Networks. CoRR abs/1711.03640 (2017) - [i4]Irem Boybat, Manuel Le Gallo, S. R. Nandakumar, Timoleon Moraitis, Thomas P. Parnell, Tomas Tuma, Bipin Rajendran, Yusuf Leblebici, Abu Sebastian, Evangelos Eleftheriou:
Neuromorphic computing with multi-memristive synapses. CoRR abs/1711.06507 (2017) - [i3]S. R. Nandakumar, Manuel Le Gallo, Irem Boybat, Bipin Rajendran, Abu Sebastian, Evangelos Eleftheriou:
Mixed-precision training of deep neural networks using computational memory. CoRR abs/1712.01192 (2017) - 2016
- [j3]Bipin Rajendran, Fabien Alibart:
Neuromorphic Computing Based on Emerging Memory Technologies. IEEE J. Emerg. Sel. Topics Circuits Syst. 6(2): 198-211 (2016) - [c21]Bipin Rajendran, Pulkit Tandon, Yash H. Malviya:
Efficient and Robust Spiking Neural Circuit for Navigation Inspired by Echolocating Bats. NIPS 2016: 938-946 - 2015
- [c20]Shruti R. Kulkarni, Bipin Rajendran:
Scalable Digital CMOS Architecture for Spike Based Supervised Learning. EANN 2015: 149-158 - [c19]Prashant J. Nair, Chia-Chen Chou, Bipin Rajendran, Moinuddin K. Qureshi:
Reducing read latency of phase change memory via early read and Turbo Read. HPCA 2015: 309-319 - [c18]John Demme, Bipin Rajendran, Steven M. Nowick, Simha Sethumadhavan:
Increasing reconfigurability with memristive interconnects. ICCD 2015: 351-358 - [c17]Navin Anwani, Bipin Rajendran:
NormAD - Normalized Approximate Descent based supervised learning rule for spiking neurons. IJCNN 2015: 1-8 - [c16]Chaitanya Prasad N, Krishnakant V. Saboo, Bipin Rajendran:
Composer classification based on temporal coding in adaptive spiking neural networks. IJCNN 2015: 1-8 - [c15]Shibani Santurkar, Bipin Rajendran:
C. elegans chemotaxis inspired neuromorphic circuit for contour tracking and obstacle avoidance. IJCNN 2015: 1-8 - [c14]Sushrut Thorat, Bipin Rajendran:
Arithmetic computing via rate coding in neural circuits with spike-triggered adaptive synapses. IJCNN 2015: 1-8 - [c13]Chirag Shetty, Sri Nitchith, Rishabh Rawat, S. R. Nandakumar, Pritesh Shah, Shruti R. Kulkarni, Bipin Rajendran:
Live demonstration: Spiking neural circuit based navigation inspired by C. elegans thermotaxis. ISCAS 2015: 1905 - [c12]Aditi Kothiyal, Bipin Rajendran, Sahana Murthy:
Delayed Guidance: A Teaching-Learning Strategy to Develop Ill-Structured Problem Solving Skills in Engineering. LaTiCE 2015: 164-171 - [c11]Bipin Rajendran, Udaya S. Ganguly, Manan Suri:
Tutorial T1: Neuromorphic Computing - Algorithms, Devices and Systems. VLSID 2015: 1-2 - 2014
- [c10]Ashish Bora, Arjun Rao, Bipin Rajendran:
Mimicking the worm - An adaptive spiking neural circuit for contour tracking inspired by C. Elegans thermotaxis. IJCNN 2014: 2079-2086 - [c9]Aniket Singha, Bhaskaran Muralidharan, Bipin Rajendran:
Analog memristive time dependent learning using discrete nanoscale RRAM devices. IJCNN 2014: 2248-2255 - [c8]Abhinav Anand, Aditi Kothiyal, Bipin Rajendran, Sahana Murthy:
Guided Problem Solving and Group Programming: A Technology-Enhanced Teaching-Learning Strategy for Engineering Problem Solving. T4E 2014: 126-133 - [i2]Shibani Santurkar, Bipin Rajendran:
A neural circuit for navigation inspired by C. elegans Chemotaxis. CoRR abs/1410.7881 (2014) - [i1]Shibani Santurkar, Bipin Rajendran:
Sub-threshold CMOS Spiking Neuron Circuit Design for Navigation Inspired by C. elegans Chemotaxis. CoRR abs/1410.7883 (2014) - 2013
- [j2]Bryan L. Jackson, Bipin Rajendran, Gregory S. Corrado, Matthew J. Breitwisch, Geoffrey W. Burr, Roger Cheek, Kailash Gopalakrishnan, Simone Raoux, Charles T. Rettner, Alvaro Padilla, Alejandro G. Schrott, Rohit S. Shenoy, Bülent N. Kurdi, Chung Hon Lam, Dharmendra S. Modha:
Nanoscale electronic synapses using phase change devices. ACM J. Emerg. Technol. Comput. Syst. 9(2): 12:1-12:20 (2013) - [c7]Bipin Rajendran, Albert K. Henning, Brian Cronquist, Zvi Or-Bach:
Pulsed laser annealing: A scalable and practical technology for monolithic 3D IC. 3DIC 2013: 1-5 - [c6]Bipin Rajendran:
Embedded tutorial - Can silicon machines match the efficiency of the human brain? VLSI Design 2013 - 2012
- [c5]Manu Awasthi, Manjunath Shevgoor, Kshitij Sudan, Bipin Rajendran, Rajeev Balasubramonian, Viji Srinivasan:
Efficient scrub mechanisms for error-prone emerging memories. HPCA 2012: 15-26 - 2011
- [b1]Moinuddin K. Qureshi, Sudhanva Gurumurthi, Bipin Rajendran:
Phase Change Memory: From Devices to Systems. Synthesis Lectures on Computer Architecture, Morgan & Claypool Publishers 2011, ISBN 978-3-031-00607-4 - [c4]Jae-sun Seo, Bernard Brezzo, Yong Liu, Benjamin D. Parker, Steven K. Esser, Robert K. Montoye, Bipin Rajendran, José A. Tierno, Leland Chang, Dharmendra S. Modha, Daniel J. Friedman:
A 45nm CMOS neuromorphic chip with a scalable architecture for learning in networks of spiking neurons. CICC 2011: 1-4 - 2010
- [j1]H.-S. Philip Wong, Simone Raoux, SangBum Kim, Jiale Liang, John P. Reifenberg, Bipin Rajendran, Mehdi Asheghi, Kenneth E. Goodson:
Phase Change Memory. Proc. IEEE 98(12): 2201-2227 (2010) - [c3]Luis Alfonso Lastras-Montaño, Michele Franceschini, Bipin Rajendran, C. Lam:
Coding for sensing in Content Addressable Memories. ISIT 2010: 1923-1927
2000 – 2009
- 2004
- [c2]Bipin Rajendran, Pawan Kapur, Krishna Saraswat, R. Fabian W. Pease:
Self-consistent power/performance/reliability analysis for copper interconnects. SLIP 2004: 17-22 - 2002
- [c1]Bipin Rajendran, Veerbhan Kheterpal, Abhishek Das, Jayanta Majumder, Chittaranjan A. Mandal, P. P. Chakrabarti:
Timing analysis of tree-like RLC circuits. ISCAS (4) 2002: 838-841
Coauthor Index
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