LIU Weichen

Appointment: Nanyang Assistant Professor

Research topics:
• Embedded and Real-Time Systems
• Many-Core Systems
• Electronic/Photonic Network-on-Chip
• Machine Learning Acceleration
• Computer Architecture

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1,011 to 1,020 of 1,026 Results

trans_googlenet_scale.py Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems Python Source Code - 15.9 KB - MD5: eb5def9be416ecbeb4d3f35856b14a0e
trans_resnet.py Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems Python Source Code - 9.4 KB - MD5: beb45d088198e1ffd6ca0d4db55b363c
trans_vgg19_half.py Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems Python Source Code - 7.3 KB - MD5: b520820fe7a477d349b4a2ec81b18f2d
trans_vgg19.py Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems Python Source Code - 6.8 KB - MD5: 84507eaff9691c96a6a3806dd803924c
vgg.py Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems Python Source Code - 3.9 KB - MD5: 9bdf5811eb5fcccc8c14c8edcdfd3bed
vgg.py Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems Python Source Code - 2.4 KB - MD5: e03fa18983a2524a824b73f8f4660dda
vgg_torch.py Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems Python Source Code - 2.7 KB - MD5: d291dc48bd5a253a62e123af35e3dbc6
y_i.tab Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems Tabular Data - 172.0 KB - 1 Variables, 5503 Observations - UNF:6:+jmG0vdNb5kvT4IJ3OJAeA==
Huai Shuo (Nanyang Technological University) Mar 7, 2022 Appointment: PhD Student
Replication Data for: XOR-Net: An Efficient Computation Pipeline for Binary Neural Network Inference on Edge Devices Dec 21, 2020 - Zhu Shien Zhu, Shien; Duong, H. K. Luan; Liu, Weichen, 2020, "Replication Data for: XOR-Net: An Efficient Computation Pipeline for Binary Neural Network Inference on Edge Devices", https://doi.org/10.21979/N9/XEH3D1, DR-NTU (Data), V1, UNF:6:5DOBB66c624HMnkRD7Qw9g== [fileUNF] Accepted as a conference paper by IEEE International Conference on Parallel and Distributed Systems (ICPADS) 2020.

trans_googlenet_scale.py

Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems

Python Source Code - 15.9 KB -

trans_resnet.py

Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems

Python Source Code - 9.4 KB -

trans_vgg19_half.py

Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems

Python Source Code - 7.3 KB -

trans_vgg19.py

Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems

Python Source Code - 6.8 KB -

vgg.py

Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems

Python Source Code - 3.9 KB -

vgg.py

Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems

Python Source Code - 2.4 KB -

vgg_torch.py

Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems

Python Source Code - 2.7 KB -

y_i.tab

Mar 7, 2022 - ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems

Tabular Data - 172.0 KB - 1 Variables, 5503 Observations -

Huai Shuo (Nanyang Technological University)

Mar 7, 2022

Appointment: PhD Student

Replication Data for: XOR-Net: An Efficient Computation Pipeline for Binary Neural Network Inference on Edge Devices

Dec 21, 2020 - Zhu Shien

Zhu, Shien; Duong, H. K. Luan; Liu, Weichen, 2020, "Replication Data for: XOR-Net: An Efficient Computation Pipeline for Binary Neural Network Inference on Edge Devices", https://doi.org/10.21979/N9/XEH3D1, DR-NTU (Data), V1, UNF:6:5DOBB66c624HMnkRD7Qw9g== [fileUNF]

Accepted as a conference paper by IEEE International Conference on Parallel and Distributed Systems (ICPADS) 2020.

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