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Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Alphacsc ⭐ 105

Convolution dictionary learning for time-series

AutoGBT is used for AutoML in a lifelong machine learning setting to classify large volume high cardinality data streams under concept-drift. AutoGBT was developed by a joint team ('autodidact.ai') from Flytxt, Indian Institute of Technology Delhi and CSIR-CEERI as a part of NIPS 2018 AutoML for Lifelong Machine Learning Challenge.

Inpainting Gmcnn Keras ⭐ 87

Keras implementation of "Image Inpainting via Generative Multi-column Convolutional Neural Networks" paper published at NIPS 2018

An official PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language", NeurIPS 2018

Implementation for <Learning towards Minimum Hyperspherical Energy> in NIPS'18.

Weakly Supervised Dense Event Captioning in Videos, i.e. generating multiple sentence descriptions for a video in a weakly-supervised manner.

Nips 2018 Adversarial Vision Challenge ⭐ 10

Code, documents, and deployment configuration files, related to our participation in the 2018 NIPS Adversarial Vision Challenge "Robust Model Track"

Open-set Recognition with Adversarial Autoencoders

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