Gwena Cunha Sergio

Gwenaelle Cunha Sergio is a senior deep-learning software engineer at NVIDIA. Her research interests include deep learning optimization and inference acceleration, computer vision, and natural language tasks. She received her Ph.D. degree in electronic and electrical engineering from Kyungpook National University, South Korea, and her bachelor's degree from the Federal University of Rio Grande do Norte (UFRN), Brazil, during which time she also participated in the Science Without Borders exchange program at Brown University, USA.
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Posts by Gwena Cunha Sergio

Simulation / Modeling / Design

Sparsity in INT8: Training Workflow and Best Practices for NVIDIA TensorRT Acceleration

The training stage of deep learning (DL) models consists of learning numerous dense floating-point weight matrices, which results in a massive amount of... 12 MIN READ
Robotics

Accelerating Quantized Networks with the NVIDIA QAT Toolkit for TensorFlow and NVIDIA TensorRT

We’re excited to announce the NVIDIA Quantization-Aware Training (QAT) Toolkit for TensorFlow 2 with the goal of accelerating the quantized networks with... 9 MIN READ