The Temporal Robustness of Stochastic Signals
Code needed to reproduce the examples found in "The Temporal Robustness of Stochastic Signals"
Case studies:
Code needed to reproduce the examples found in "The Temporal Robustness of Stochastic Signals"
Overview
Implementation of popular bandit algorithms in batch environments.
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Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR
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PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA
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Vision Deep-Learning using Tensorflow, Keras.
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Tool for working with Y-chromosome data from YFull and FTDNA
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Line-level Handwritten Text Recognition (HTR) system implemented with TensorFlow.
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Some experiments with tennis player aging curves using Hilbert space GPs in PyMC. Only experimental for now.
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Unifying Global-Local Representations in Salient Object Detection with Transformer
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Deep Sea Treasure Environment for Multi-Objective Optimization Research
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DA2Lite is an automated model compression toolkit for PyTorch.
DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari
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traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation toolbox based on PyTorch.
traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to
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Unofficial implementation of "Coordinate Attention for Efficient Mobile Network Design"
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A simple library that implements CLIP guided loss in PyTorch.
pytorch_clip_guided_loss: Pytorch implementation of the CLIP guided loss for Text-To-Image, Image-To-Image, or Image-To-Text generation. A simple libr
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ObjectDetNet is an easy, flexible, open-source object detection framework
Getting started with the ObjectDetNet ObjectDetNet is an easy, flexible, open-source object detection framework which allows you to easily train, resu
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CSPML (crystal structure prediction with machine learning-based element substitution)
CSPML (crystal structure prediction with machine learning-based element substitution) CSPML is a unique methodology for the crystal structure predicti
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Paper: Cross-View Kernel Similarity Metric Learning Using Pairwise Constraints for Person Re-identification
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Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment
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Codebase for Time-series Generative Adversarial Networks (TimeGAN)
Codebase for Time-series Generative Adversarial Networks (TimeGAN)
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Решения, подсказки, тесты и утилиты для тренировки по алгоритмам от Яндекса.
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Simultaneous Demand Prediction and Planning
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