GANs in Action
by Jakub Langr and Vladimir Bok
Gans-in-action - Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
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GANs in Action
Deep learning with Generative Adversarial Networks by Jakub Langr and Vladimir Bok
Scene-Text-Detection-and-Recognition (Pytorch)
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Code for the paper "Offline Reinforcement Learning as One Big Sequence Modeling Problem"
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StyleGAN-Human: A Data-Centric Odyssey of Human Generation
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Exploring Relational Context for Multi-Task Dense Prediction [ICCV 2021]
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Scalable machine learning based time series forecasting
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Codebase for testing whether hidden states of neural networks encode discrete structures.
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Sample code from the Neural Networks from Scratch book.
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📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.
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Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.
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A Python framework for conversational search
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Implementation of the ICCV'21 paper Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases
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A library for differentiable nonlinear optimization.
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Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Learning with Nonignorable Nonresponses‘
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A naive ROS interface for visualDet3D.
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Segmentation Training Pipeline
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