4,461 Works

File index

Wei Chen, Zeng Huang, Nicholas Tay, Benjamin Giglio, Mengzhe Wang, Hui Wang, Zhanhong Wu, David Nicewicz & Zibo Li
file index

File index

Wei Chen, Zeng Huang, Nicholas Tay, Benjamin Giglio, Mengzhe Wang, Hui Wang, Zhanhong Wu, David Nicewicz & Zibo Li
file index

File index

Wei Chen, Zeng Huang, Nicholas Tay, Benjamin Giglio, Mengzhe Wang, Hui Wang, Zhanhong Wu, David Nicewicz & Zibo Li
file index

File index for #39 in MCF-7 and U87MG tumor models at different time points

Wei Chen, Zeng Huang, Nicholas Tay, Benjamin Giglio, Mengzhe Wang, Hui Wang, Zhanhong Wu, David Nicewicz & Zibo Li
file index

Trained ssd-resnet34 onnx model for MLPerf Cloud Inference

Mlperf
Application: Object Detection ML Task: ssd-resnet34 Framework: onnx Training Information: Quality: 0.20% Precision: fp32 Is Quantized: no Is ONNX: yes Dataset: http://images.cocodataset.org/zips/val2014.zip (resized to 1200x1200) Source Model: https://github.com/mlperf/inference/tree/master/cloud/single_stage_detector

Trained ssd-resnet34 onnx model for MLPerf Cloud Inference

Mlperf
Application: Object Detection ML Task: ssd-resnet34 Framework: onnx Training Information: Quality: 0.20% Precision: fp32 Is Quantized: no Is ONNX: yes Dataset: http://images.cocodataset.org/zips/val2014.zip (resized to 1200x1200) Source Model: https://github.com/mlperf/inference/tree/master/cloud/single_stage_detector

Trained ssd-resnet34 onnx model for MLPerf Cloud Inference

Mlperf
Application: Object Detection ML Task: ssd-resnet34 Framework: onnx Training Information: Quality: 0.20% Precision: fp32 Is Quantized: no Is ONNX: yes Dataset: http://images.cocodataset.org/zips/val2014.zip (resized to 1200x1200) Source Model: https://github.com/mlperf/inference/tree/master/cloud/single_stage_detector

Trained mobilenetv1 ONNX Model for MLPerf Cloud Inference

Https://Github.Com/Tensorflow/Models/Blob/Master/Research/Slim/Nets/Mobilenet_v1.Md
Application: Image Classification ML Task: mobilenetv1 Framework: ONNX (via tensorflow) Training Information: Quality: 70.9% Precision: fp32 Is Quantized: no Is ONNX: yes Dataset: http://www.image-net.org/challenges/LSVRC/2012/

Trained mobilenetv1 ONNX Model for MLPerf Cloud Inference

Https://Github.Com/Tensorflow/Models/Blob/Master/Research/Slim/Nets/Mobilenet_v1.Md
Application: Image Classification ML Task: mobilenetv1 Framework: ONNX (via tensorflow) Training Information: Quality: 70.9% Precision: fp32 Is Quantized: no Is ONNX: yes Dataset: http://www.image-net.org/challenges/LSVRC/2012/

Trained mobilenetv1 ONNX Model for MLPerf Cloud Inference

Https://Github.Com/Tensorflow/Models/Blob/Master/Research/Slim/Nets/Mobilenet_v1.Md
Application: Image Classification ML Task: mobilenetv1 Framework: ONNX (via tensorflow) Training Information: Quality: 70.9% Precision: fp32 Is Quantized: no Is ONNX: yes Dataset: http://www.image-net.org/challenges/LSVRC/2012/

programs and simulation schemes

Jidong Jia
Supplementary material on programs and simulation schemes. Please ensure the integrity and confidentiality.

programs and simulation schemes

Jidong Jia
Supplementary material on programs and simulation schemes. Please ensure the integrity and confidentiality.

Book of abstracts of the Scientific Colloquium 'Plant Health at the Age of Metagenomics'

Sébastien Massart, Adrian Fox, Gilles Cellier, Jaime Cubero, Guillaume Bilodeau, Diane Saunders & Kim Hammond-Kosack
New techniques allowing processing of large numbers of samples and generating huge volumes of genomic and protein data offer new opportunities to study plant pests. Rather than isolating individual molecules, in order to understand their role in the biology of an organism, it is now possible to investigate the genome as a whole, or the interactions of proteins and other metabolites as a holistic approach. These new techniques allow known pests to be studied in...

Book of abstracts of the Scientific Colloquium 'Plant Health at the Age of Metagenomics'

Sébastien Massart, Adrian Fox, Gilles Cellier, Jaime Cubero, Guillaume Bilodeau, Diane Saunders & Kim Hammond-Kosack
New techniques allowing processing of large numbers of samples and generating huge volumes of genomic and protein data offer new opportunities to study plant pests. Rather than isolating individual molecules, in order to understand their role in the biology of an organism, it is now possible to investigate the genome as a whole, or the interactions of proteins and other metabolites as a holistic approach. These new techniques allow known pests to be studied in...

CONSERVADOR Page Like Network

Celina Lerner
Interactive version of Page Like Network of Brazilian conservative Facebook Pages. Instructions: > Download the zip file
> Unzip the folder
> Open the file: PAGE_LIKE_NETWORK.html with Mozilla Firefox

Obs: As an html file, it can be read by any browser, but Mozilla Firefox is recommended for a better experience. Form: Lerner, Celina. "A mentalidade conservadora no Brasil: uma análise da interação política em redes sociais digitais" - Doctoral Thesis, PCHS/UFABC ,2019

CONSERVADOR Page Like Network

Celina Lerner
Interactive version of Page Like Network of Brazilian conservative Facebook Pages. Instructions: > Download the zip file
> Unzip the folder
> Open the file: PAGE_LIKE_NETWORK.html with Mozilla Firefox

Obs: As an html file, it can be read by any browser, but Mozilla Firefox is recommended for a better experience. Form: Lerner, Celina. "A mentalidade conservadora no Brasil: uma análise da interação política em redes sociais digitais" - Doctoral Thesis, PCHS/UFABC ,2019

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