Geng Yuan
Orcid: 0000-0001-9844-992X
According to our database1,
Geng Yuan
authored at least 86 papers
between 2017 and 2024.
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Bibliography
2024
CoRR, 2024
CoRR, 2024
SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024
DACO: Pursuing Ultra-low Power Consumption via DNN-Adaptive CPU-GPU CO-optimization on Mobile Devices.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024
2023
IEEE Trans. Computers, May, 2023
MTS-LOF: Medical Time-Series Representation Learning via Occlusion-Invariant Features.
CoRR, 2023
Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges.
CoRR, 2023
A Life-Cycle Energy and Inventory Analysis of Adiabatic Quantum-Flux-Parametron Circuits.
CoRR, 2023
Uncertainty Quantification in Neural Networks Using Stochastic Differential Equations.
Proceedings of the 62nd Annual Conference of the Society of Instrument and Control Engineers, 2023
PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
HotBEV: Hardware-oriented Transformer-based Multi-View 3D Detector for BEV Perception.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
SupeRBNN: Randomized Binary Neural Network Using Adiabatic Superconductor Josephson Devices.
Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, 2023
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
MOC: Multi-Objective Mobile CPU-GPU Co-Optimization for Power-Efficient DNN Inference.
Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023
ESRU: Extremely Low-Bit and Hardware-Efficient Stochastic Rounding Unit Design for Low-Bit DNN Training.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023
Proceedings of the 2023 Workshop on Advanced Multimedia Computing for Smart Manufacturing and Engineering, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework.
ACM Trans. Embed. Comput. Syst., September, 2022
Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration.
ACM Trans. Design Autom. Electr. Syst., 2022
IEEE Trans. Neural Networks Learn. Syst., 2022
DeltaFS: Pursuing Zero Update Overhead via Metadata-Enabled Delta Compression for Log-structured File System on Mobile Devices.
CoRR, 2022
An Automatically Privacy Protection Solution for Implementing the Right to Be Forgotten in Embedded System.
IEEE Access, 2022
Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022
Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022
Proceedings of the IEEE International Symposium on Circuits and Systems, 2022
Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Auto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization.
Proceedings of the 32nd International Conference on Field-Programmable Logic and Applications, 2022
You Already Have It: A Generator-Free Low-Precision DNN Training Framework Using Stochastic Rounding.
Proceedings of the Computer Vision - ECCV 2022, 2022
Proceedings of the Computer Vision - ECCV 2022, 2022
Fault-Tolerant Deep Neural Networks for Processing-In-Memory based Autonomous Edge Systems.
Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 2022
FPGA-aware automatic acceleration framework for vision transformer with mixed-scheme quantization: late breaking results.
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022
Hardware-efficient stochastic rounding unit design for DNN training: late breaking results.
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022
Proceedings of the IEEE 15th International Conference on Cloud Computing, 2022
2021
CoRR, 2021
CoRR, 2021
Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search.
Proceedings of the 27th IEEE Real-Time and Embedded Technology and Applications Symposium, 2021
Work in Progress: Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework.
Proceedings of the 27th IEEE Real-Time and Embedded Technology and Applications Symposium, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI.
Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021
FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator.
Proceedings of the 48th ACM/IEEE Annual International Symposium on Computer Architecture, 2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
ClickTrain: efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning.
Proceedings of the ICS '21: 2021 International Conference on Supercomputing, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021
HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU.
Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021
TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021
NPAS: A Compiler-Aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
An Explainable Convolutional Neural Networks for Automatic Segmentation of the Left Ventricle in Cardiac MRI.
Proceedings of CECNet 2021, 2021
Proceedings of the ASPDAC '21: 26th Asia and South Pacific Design Automation Conference, 2021
A Compression-Compilation Co-Design Framework Towards Real-Time Object Detection on Mobile Devices.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
6.7ms on Mobile with over 78% ImageNet Accuracy: Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration.
CoRR, 2020
An Efficient End-to-End Deep Learning Training Framework via Fine-Grained Pattern-Based Pruning.
CoRR, 2020
Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization.
CoRR, 2020
SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency.
CoRR, 2020
Proceedings of the 33rd IEEE International System-on-Chip Conference, 2020
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020
Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation.
Proceedings of the 25th Asia and South Pacific Design Automation Conference, 2020
2019
A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation.
CoRR, 2019
CoRR, 2019
ResNet Can Be Pruned 60x: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning.
CoRR, 2019
ResNet Can Be Pruned 60×: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning.
Proceedings of the IEEE/ACM International Symposium on Nanoscale Architectures, 2019
An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM.
Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019
2018
An area and energy efficient design of domain-wall memory-based deep convolutional neural networks using stochastic computing.
Proceedings of the 19th International Symposium on Quality Electronic Design, 2018
Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs.
Proceedings of the 2018 on Great Lakes Symposium on VLSI, 2018
Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices.
CoRR, 2017
Proceedings of the IEEE 60th International Midwest Symposium on Circuits and Systems, 2017
CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices.
Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, 2017