94 results on '"Rajendran, Bipin"'
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2. Ultra-low power neuromorphic obstacle detection using a two-dimensional materials-based subthreshold transistor
3. Memristive devices for spiking neural networks
4. List of contributors
5. Memristive devices for deep learning applications
6. Role of resistive memory devices in brain-inspired computing
7. Memristive devices as computational memory
8. Preface
9. Acceleration of Convolutional Networks Using Nanoscale Memristive Devices
10. Modeling and Simulation of 1/f Noise During Threshold Switching for Phase Change Memory
11. Neuromorphic Accelerator for Deep Spiking Neural Networks with NVM Crossbar Arrays
12. Spiking Generative Adversarial Networks With a Neural Network Discriminator: Local Training, Bayesian Models, and Continual Meta-Learning
13. Editorial: Neuro-inspired computing for next-gen AI: Computing model, architectures and learning algorithms
14. Erratum to: Novel Biomimetic Si Devices for Neuromorphic Computing Architecture
15. Novel Biomimetic Si Devices for Neuromorphic Computing Architecture
16. Scalable Digital CMOS Architecture for Spike Based Supervised Learning
17. Fast On-Device Adaptation for Spiking Neural Networks Via Online-Within-Online Meta-Learning
18. Hybrid In-Memory Computing Architecture for the Training of Deep Neural Networks
19. ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning
20. Storage and System Design With Emerging Non-Volatile Memories
21. Wear Leveling for Durability
22. Phase Change Memory
23. Next Generation Memory Technologies
24. Wear Leveling Under Adversarial Settings
25. Error Resilience in Phase Change Memories
26. Tolerating Slow Writes in PCM
27. Architecting PCM for Main Memories
28. Memristors—From In‐Memory Computing, Deep Learning Acceleration, and Spiking Neural Networks to the Future of Neuromorphic and Bio‐Inspired Computing
29. Accurate deep neural network inference using computational phase-change memory
30. Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses
31. Mixed-Precision Deep Learning Based on Computational Memory
32. Bio-mimetic synaptic plasticity and learning in a sub-500 mV Cu/SiO2/W memristor
33. An On-Chip Learning Accelerator for Spiking Neural Networks using STT-RAM Crossbar Arrays
34. Training multi-layer spiking neural networks using NormAD based spatio-temporal error backpropagation
35. Kinetic Monte Carlo Simulation of Interface-Controlled Hafnia-Based Resistive Memory
36. Phase-Change Memory Models for Deep Learning Training and Inference
37. Learning Algorithms and Signal Processing for Brain-Inspired Computing [From the Guest Editors]
38. Low-Power Neuromorphic Hardware for Signal Processing Applications: A Review of Architectural and System-Level Design Approaches
39. Neuromorphic Hardware Accelerator for SNN Inference based on STT-RAM Crossbar Arrays
40. Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients
41. Building Next-Generation AI systems: Co-Optimization of Algorithms, Architectures, and Nanoscale Memristive Devices
42. Stochastic learning in deep neural networks based on nanoscale PCMO device characteristics
43. A phase-change memory model for neuromorphic computing
44. Well-Posed Verilog-A Compact Model for Phase Change Memory
45. Building Brain-Inspired Computing Systems: Examining the Role of Nanoscale Devices
46. Spiking neural networks for handwritten digit recognition—Supervised learning and network optimization
47. Neuromorphic computing with multi-memristive synapses
48. Adversarial Training for Probabilistic Spiking Neural Networks
49. Live Demonstration: Image Classification Using Bio-inspired Spiking Neural Networks
50. Training Probabilistic Spiking Neural Networks with First- To-Spike Decoding
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