The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...

Multi-agent systems are widely applicable to real-world applications ranging from warehouse automation to environmental monitoring, autonomous driving, and even computer game simulations. Compared to ...

Same as traditional autoencoders, VAE architecture has two parts: an encoder and a decoder. Traditional AE models map inputs into a latent-space vector and reconstruct the output from this vector. VAE ...

2021 NeurIPS Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection 2021 NeurIPS Exploring the Limits of Out-of-Distribution Detection 2021 NeurIPS Locally Most ...

Department of Chemistry, University of Toronto, Toronto, ON M5S 3H6, Canada Department of Computer Science, University of Toronto, Toronto, ON M5S 2E4, Canada Vector Institute for Artificial ...

日本北海道大学提出 Gromov-Wasserstein Autoencoders（GWAE），将变分自编码器 Variational Autoencoder (VAE) 重写为数据和表示之间的最优传输的灵活表征学习框架。 学习高维数据的低维表示是无监督学习中的基本任务，因为这种表示简明地捕捉了数据的本质，并且使得执行 ...

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...

Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more expressive variational family, the inverse ...