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HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021, p.5189-5198

2021

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Pre-Defined Sparsity for Low-Complexity Convolutional Neural Networks

IEEE transactions on computers, 2020-07, Vol.69 (7), p.1045-1058

2020

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Guest Editorial: Special Issue on Learning, Optimization, and Implementation for Circuits and Systems Driven by Artificial Intelligence

IEEE transactions on circuits and systems. I, Regular papers, 2024-05, Vol.71 (5), p.1965-1968

2024

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Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking Neural Networks?

2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2022, p.718-723

2022

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Spike-Thrift: Towards Energy-Efficient Deep Spiking Neural Networks by Limiting Spiking Activity via Attention-Guided Compression

2021 IEEE Winter Conference on Applications of Computer Vision (WACV), 2021, p.3952-3961

2021

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ACE-SNN: Algorithm-Hardware Co-design of Energy-Efficient & Low-Latency Deep Spiking Neural Networks for 3D Image Recognition

Frontiers in neuroscience, 2022-04, Vol.16, p.815258

2022

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On the Security of Sequential Logic Locking Against Oracle-Guided Attacks

IEEE transactions on computer-aided design of integrated circuits and systems, 2023-11, Vol.42 (11), p.1-1

2023

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Converting Flip-Flop to Clock-Gated 3-Phase Latch-Based Designs Using Graph-Based Retiming

IEEE transactions on computer-aided design of integrated circuits and systems, 2022-04, Vol.41 (4), p.979-992

2022

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A processing-in-pixel-in-memory paradigm for resource-constrained TinyML applications

Scientific reports, 2022-08, Vol.12 (1), p.14396-14396, Article 14396

2022

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Metastability in Superconducting Single Flux Quantum (SFQ) Logic

IEEE transactions on circuits and systems. I, Regular papers, 2021-05, Vol.68 (5), p.1990-2002

2021

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Programming memristor arrays with arbitrarily high precision for analog computing

Science (American Association for the Advancement of Science), 2024-02, Vol.383 (6685), p.903-910

2024

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SERAD: Soft Error Resilient Asynchronous Design Using a Bundled Data Protocol

IEEE transactions on circuits and systems. I, Regular papers, 2020-05, Vol.67 (5), p.1667-1677

2020

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A Robust and Self-Adaptive Clocking Technique for SFQ Circuits

IEEE transactions on applied superconductivity, 2018-10, Vol.28 (7), p.1-11

2018

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BMPQ: Bit-Gradient Sensitivity-Driven Mixed-Precision Quantization of DNNs from Scratch

2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2022, p.588-591

2022

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RNA-ViT: Reduced-Dimension Approximate Normalized Attention Vision Transformers for Latency Efficient Private Inference

2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 2023, p.1-9

2023

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SystemVerilog Modeling of SFQ and AQFP Circuits

IEEE transactions on applied superconductivity, 2020-03, Vol.30 (2), p.1-13

2020

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Optimizing (HC)[Formula Omitted] LC, A Robust Clock Distribution Network For SFQ Circuits

IEEE transactions on applied superconductivity, 2020-01, Vol.30 (1), p.1

2020

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ViTA: A Vision Transformer Inference Accelerator for Edge Applications

2023 IEEE International Symposium on Circuits and Systems (ISCAS), 2023, p.1-5

2023

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Bridging the Gap Between Spiking Neural Networks & LSTMs for Latency & Energy Efficiency

2023 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2023, p.1-6

2023

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GF-Flush: A GF(2) Algebraic Attack on Dynamically Secured Scan Chains

2021 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT), 2021, p.1-6

2021

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Single Flux Quantum (SFQ) First-in-First-Out (FIFO) Synchronizers: New Designs and Paradigms

IEEE transactions on applied superconductivity, 2020-10, Vol.30 (7), p.1-8

2020

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Self-Attentive Pooling for Efficient Deep Learning

2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023, p.3963-3972

2023

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FLOAT: Fast Learnable Once-for-All Adversarial Training for Tunable Trade-off between Accuracy and Robustness

2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023, p.2348-2357

2023

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Neuromorphic-P2M: processing-in-pixel-in-memory paradigm for neuromorphic image sensors

Frontiers in neuroinformatics, 2023-05, Vol.17, p.1144301-1144301

2023

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Modeling and Characterization of Metastability in Single Flux Quantum (SFQ) Synchronizers

2020 IEEE International Symposium on Circuits and Systems (ISCAS), 2020, p.1-5

2020

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HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise

Pre-Defined Sparsity for Low-Complexity Convolutional Neural Networks

Guest Editorial: Special Issue on Learning, Optimization, and Implementation for Circuits and Systems Driven by Artificial Intelligence

Can Deep Neural Networks be Converted to Ultra Low-Latency Spiking Neural Networks?

Spike-Thrift: Towards Energy-Efficient Deep Spiking Neural Networks by Limiting Spiking Activity via Attention-Guided Compression

ACE-SNN: Algorithm-Hardware Co-design of Energy-Efficient & Low-Latency Deep Spiking Neural Networks for 3D Image Recognition

On the Security of Sequential Logic Locking Against Oracle-Guided Attacks

Converting Flip-Flop to Clock-Gated 3-Phase Latch-Based Designs Using Graph-Based Retiming

A processing-in-pixel-in-memory paradigm for resource-constrained TinyML applications

Metastability in Superconducting Single Flux Quantum (SFQ) Logic

Programming memristor arrays with arbitrarily high precision for analog computing

SERAD: Soft Error Resilient Asynchronous Design Using a Bundled Data Protocol

A Robust and Self-Adaptive Clocking Technique for SFQ Circuits

BMPQ: Bit-Gradient Sensitivity-Driven Mixed-Precision Quantization of DNNs from Scratch

RNA-ViT: Reduced-Dimension Approximate Normalized Attention Vision Transformers for Latency Efficient Private Inference

SystemVerilog Modeling of SFQ and AQFP Circuits

Optimizing (HC)[Formula Omitted] LC, A Robust Clock Distribution Network For SFQ Circuits

ViTA: A Vision Transformer Inference Accelerator for Edge Applications

Bridging the Gap Between Spiking Neural Networks & LSTMs for Latency & Energy Efficiency

GF-Flush: A GF(2) Algebraic Attack on Dynamically Secured Scan Chains

Single Flux Quantum (SFQ) First-in-First-Out (FIFO) Synchronizers: New Designs and Paradigms

Self-Attentive Pooling for Efficient Deep Learning

FLOAT: Fast Learnable Once-for-All Adversarial Training for Tunable Trade-off between Accuracy and Robustness

Neuromorphic-P2M: processing-in-pixel-in-memory paradigm for neuromorphic image sensors

Modeling and Characterization of Metastability in Single Flux Quantum (SFQ) Synchronizers

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