Icml 2020 Collection

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“Implementations of few-shot object detection benchmarks”

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“code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"”

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“Code base for the precision, recall, density, and coverage metrics for generative models. ICML 2020.”

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“A list of the top 10 computer vision papers in 2020 with video demos, articles, code and paper reference.”

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“Official Pytorch implementation of ReBias (Learning De-biased Representations with Biased Representations), ICML 2020”

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“[ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels”

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“Repository of the ICML 2020 paper "Set Functions for Time Series"”

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“Soft Threshold Weight Reparameterization for Learnable Sparsity”

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“Official implementation of the paper Stochastic Latent Residual Video Prediction”

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“Code for reproducing results in ICML 2020 paper "PackIt: A Virtual Environment for Geometric Planning"”

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“Benchmarking continual learning techniques for Human Activity Recognition data. We offer interesting insights on how the performance techniques vary with a domain other than images.”