Sergey Zagoruyko (szagoruyko)

szagoruyko

Geek Repo

Company:MTS AI

Location:London

Home Page:https://szagoruyko.github.io

Twitter:@szagoruyko5

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Organizations
torch

Sergey Zagoruyko's starred repositories

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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visdom

A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

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sonnet

TensorFlow-based neural network library

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OpenNMT-py

Open Source Neural Machine Translation and (Large) Language Models in PyTorch

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ssd.pytorch

A PyTorch Implementation of Single Shot MultiBox Detector

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pytorch-examples

Simple examples to introduce PyTorch

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fairseq-lua

Facebook AI Research Sequence-to-Sequence Toolkit

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ResNeXt

Implementation of a classification framework from the paper Aggregated Residual Transformations for Deep Neural Networks

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attention-transfer

Improving Convolutional Networks via Attention Transfer (ICLR 2017)

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scikit-cuda

Python interface to GPU-powered libraries

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crayon

A language-agnostic interface to TensorBoard

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tensorboard_logger

Log TensorBoard events without touching TensorFlow

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diracnets

Training Very Deep Neural Networks Without Skip-Connections

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tikz_cnn

Macro to draw architecture of convolutional neural nets in tikz.

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optnet

OptNet: Differentiable Optimization as a Layer in Neural Networks

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topicsne

t-SNE experiments in pytorch

ARAE

Code for the paper "Adversarially Regularized Autoencoders (ICML 2018)" by Zhao, Kim, Zhang, Rush and LeCun

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pytorch_fft

PyTorch wrapper for FFTs

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variational-dropout-sparsifies-dnn

Sparse Variational Dropout, ICML 2017

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pyscatwave

Fast Scattering Transform with CuPy/PyTorch

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shake-shake

2.86% and 15.85% on CIFAR-10 and CIFAR-100

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tensorflow-model-zoo.torch

InceptionV3, InceptionV4, Inception-Resnet pretrained models for Torch7 and PyTorch

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deep-smile-warp

DeepWarp for Facial Expression Manipulation

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neural-style-audio-torch

Torch implementation for audio neural style.

mlogger

a lightweight and simple logger for Machine Learning

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wide-residual-network

Wide-residual network implementations. Best result for cifar10(97.12%), cifar100(84.12%), and other kaggle challenges

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