Archives for Generative Adversarial Networks
Algorithms can help you create your own art, and there are plenty of crash courses and full-time programs to help you learn the art of coding in AI
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The basic premise of BigGAN is simple; scale-up GAN training to benefit from larger models and larger batches.
The post Hands-on Guide to BigGAN with Python code appeared first on Analytics India Magazine.
The basic premise of BigGAN is simple; scale-up GAN training to benefit from larger models and larger batches.
The post Hands-on Guide to BigGAN with Python code appeared first on Analytics India Magazine.
What Is A Time Series GAN?
Identifying anomalies in time series data can be daunting, thanks to the vague definition of anomalies, lack of labelled data, and highly complex temporal correlations. Currently, the machine learning method used for anomaly detection faces scalability and portability issues, resulting in false-positives. And, therein lies the problem. In a recent paper, MIT researchers proposed an…
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Following MIT, researchers at NVIDIA have recently developed a new augmented method for training Generative Adversarial Networks (GANs) with a limited amount of data. The approach is an adaptive discriminator augmentation mechanism that significantly stabilised training in limited data regimes. Machine learning models are data-hungry. As a matter of fact, in the past few years,…
The post A New Trend Of Training GANs With Less Data: NVIDIA Joins The Gang appeared first on Analytics India Magazine.