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EvoApprox8b: Library of Approximate Adders and Multipliers for Circuit Design and Benchmarking of Approximation Methods

Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017, 2017, p.258-261

2017

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Improving the Accuracy and Hardware Efficiency of Neural Networks Using Approximate Multipliers

IEEE transactions on very large scale integration (VLSI) systems, 2020-02, Vol.28 (2), p.317-328

2020

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RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks

IEEE access, 2022, Vol.10, p.1-1

2022

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SagTree: Towards efficient mutation in evolutionary circuit approximation

Swarm and evolutionary computation, 2022-03, Vol.69, p.100986, Article 100986

2022

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Energy Complexity Model for Convolutional Neural Networks

Artificial Neural Networks and Machine Learning - ICANN 2023, 2023, Vol.14263, p.186-198

2023

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Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error

IEEE transactions on very large scale integration (VLSI) systems, 2018-11, Vol.26 (11), p.2572-2576

2018

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Automated Verifiability-Driven Design of Approximate Circuits: Exploiting Error Analysis

2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2024, p.1-6

2024

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DESCNet: Developing Efficient Scratchpad Memories for Capsule Network Hardware

IEEE transactions on computer-aided design of integrated circuits and systems, 2021-09, Vol.40 (9), p.1768-1781

2021

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Acceleration Techniques for Automated Design of Approximate Convolutional Neural Networks

IEEE journal on emerging and selected topics in circuits and systems, 2023-03, Vol.13 (1), p.212-224

2023

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Design of power-efficient approximate multipliers for approximate artificial neural networks

2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2016, p.1-7

2016

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Evolutionary Neural Architecture Search Supporting Approximate Multipliers

Genetic Programming, p.82-97

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Evolutionary Design of Reduced Precision Preprocessor for Levodopa-Induced Dyskinesia Classifier

Parallel Problem Solving from Nature – PPSN XVII, p.491-504

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Automated Circuit Approximation Method Driven by Data Distribution

2019 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2019, p.96-101

2019

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ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining

2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2019, p.1-8

2019

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TFApprox: Towards a Fast Emulation of DNN Approximate Hardware Accelerators on GPU

2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2020, p.294-297

2020

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ReD-CaNe: A Systematic Methodology for Resilience Analysis and Design of Capsule Networks under Approximations

2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2020, p.1205-1210

2020

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autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components

2019 56th ACM/IEEE Design Automation Conference (DAC), 2019, p.1-6

2019

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Adaptive verifiability-driven strategy for evolutionary approximation of arithmetic circuits

Applied soft computing, 2020-10, Vol.95, p.106466, Article 106466

2020

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Designing Approximate Arithmetic Circuits with Combined Error Constraints

2022 25th Euromicro Conference on Digital System Design (DSD), 2022, p.785-792

2022

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Xel-FPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems

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

2023

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ApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems

2020 57th ACM/IEEE Design Automation Conference (DAC), 2020, p.1-6

2020

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Approximation of Hardware Accelerators driven by Machine-Learning Models : (Embedded Tutorial)

2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS), 2023, p.91-92

Mrazek, Vojtech

2023

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Optimization of BDD-based Approximation Error Metrics Calculations

2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 2022, p.86-91

Mrazek, Vojtech

2022

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Evolutionary Design of Transistor Level Digital Circuits Using Discrete Simulation

Genetic Programming, p.66-77

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Towards low power approximate DCT architecture for HEVC standard

Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017, 2017, p.1576-1581

2017

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EvoApprox8b: Library of Approximate Adders and Multipliers for Circuit Design and Benchmarking of Approximation Methods

Improving the Accuracy and Hardware Efficiency of Neural Networks Using Approximate Multipliers

RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks

SagTree: Towards efficient mutation in evolutionary circuit approximation

Energy Complexity Model for Convolutional Neural Networks

Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error

Automated Verifiability-Driven Design of Approximate Circuits: Exploiting Error Analysis

DESCNet: Developing Efficient Scratchpad Memories for Capsule Network Hardware

Acceleration Techniques for Automated Design of Approximate Convolutional Neural Networks

Design of power-efficient approximate multipliers for approximate artificial neural networks

Evolutionary Neural Architecture Search Supporting Approximate Multipliers

Evolutionary Design of Reduced Precision Preprocessor for Levodopa-Induced Dyskinesia Classifier

Automated Circuit Approximation Method Driven by Data Distribution

ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining

TFApprox: Towards a Fast Emulation of DNN Approximate Hardware Accelerators on GPU

ReD-CaNe: A Systematic Methodology for Resilience Analysis and Design of Capsule Networks under Approximations

autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components

Adaptive verifiability-driven strategy for evolutionary approximation of arithmetic circuits

Designing Approximate Arithmetic Circuits with Combined Error Constraints

Xel-FPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems

ApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems

Approximation of Hardware Accelerators driven by Machine-Learning Models : (Embedded Tutorial)

Optimization of BDD-based Approximation Error Metrics Calculations

Evolutionary Design of Transistor Level Digital Circuits Using Discrete Simulation

Towards low power approximate DCT architecture for HEVC standard

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