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 ...
Abstract: This paper presents a novel approach for multimodal data fusion based on the Vector-Quantized Variational Autoencoder (VQVAE) architecture. The proposed method is simple yet effective in ...
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 ...
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 ...
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