115 Python Mnist-vae-scaling Libraries

Recognize Handwritten Digits using Deep Learning on the browser itself.

MNIST on the Web An attempt to predict MNIST handwritten digits from my PyTorch model from the browser (client-side) and not from the server, with the

7 May 28, 2022

Attention mechanism with MNIST dataset

[TensorFlow] Attention mechanism with MNIST dataset Usage $ python run.py Result Training Loss graph. Test Each figure shows input digit, attention ma

12 Jun 10, 2022

Extract MNIST handwritten digits dataset binary file into bmp images

MNIST-dataset-extractor Extract MNIST handwritten digits dataset binary file into bmp images More info at http://yann.lecun.com/exdb/mnist/ Dependenci

6 May 24, 2021

Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Parallel Tacotron2 Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

170 Dec 27, 2022

Official code for "End-to-End Optimization of Scene Layout" -- including VAE, Diff Render, SPADE for colorization (CVPR 2020 Oral)

End-to-End Optimization of Scene Layout Code release for: End-to-End Optimization of Scene Layout CVPR 2020 (Oral) Project site, Bibtex For help conta

41 Dec 9, 2022

Image-Scaling Attacks and Defenses

Image-Scaling Attacks & Defenses This repository belongs to our publication: Erwin Quiring, David Klein, Daniel Arp, Martin Johns and Konrad Rieck. Ad

163 Nov 21, 2022

VideoGPT: Video Generation using VQ-VAE and Transformers

VideoGPT: Video Generation using VQ-VAE and Transformers [Paper][Website][Colab][Gradio Demo] We present VideoGPT: a conceptually simple architecture

470 Dec 30, 2022

A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models, using the tools and APIs you know and love from the PyData stack (such as numpy, pandas, and scikit-learn).

This tutorial's purpose is to introduce Pythonistas to methods for scaling their data science and machine learning work to larger datasets and larger models, using the tools and APIs they know and love from the PyData stack (such as numpy, pandas, and scikit-learn).

102 Nov 10, 2022

Elliot is a comprehensive recommendation framework that analyzes the recommendation problem from the researcher's perspective.

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

Information Systems Lab @ Polytechnic University of Bari

215 Nov 29, 2022

Diverse Image Captioning with Context-Object Split Latent Spaces (NeurIPS 2020)

Diverse Image Captioning with Context-Object Split Latent Spaces This repository is the PyTorch implementation of the paper: Diverse Image Captioning

34 Nov 21, 2022

Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones

HaloNet - Pytorch Implementation of the Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones. This re

189 Nov 22, 2022

Python Mnist-vae-scaling Resources

Python mnist-vae-scaling Libraries

Recognize Handwritten Digits using Deep Learning on the browser itself.

Attention mechanism with MNIST dataset

Extract MNIST handwritten digits dataset binary file into bmp images

Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Official code for "End-to-End Optimization of Scene Layout" -- including VAE, Diff Render, SPADE for colorization (CVPR 2020 Oral)

Image-Scaling Attacks and Defenses

VideoGPT: Video Generation using VQ-VAE and Transformers

A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models, using the tools and APIs you know and love from the PyData stack (such as numpy, pandas, and scikit-learn).

Elliot is a comprehensive recommendation framework that analyzes the recommendation problem from the researcher's perspective.

Diverse Image Captioning with Context-Object Split Latent Spaces (NeurIPS 2020)

Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones

CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"

PyTorch package for the discrete VAE used for DALL·E.

Machine learning, in numpy

Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow

Python Mnist-vae-scaling Resources

Python mnist-vae-scaling Libraries

Recognize Handwritten Digits using Deep Learning on the browser itself.

Attention mechanism with MNIST dataset

Extract MNIST handwritten digits dataset binary file into bmp images

Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Official code for "End-to-End Optimization of Scene Layout" -- including VAE, Diff Render, SPADE for colorization (CVPR 2020 Oral)

Image-Scaling Attacks and Defenses

VideoGPT: Video Generation using VQ-VAE and Transformers

A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models, using the tools and APIs you know and love from the PyData stack (such as numpy, pandas, and scikit-learn).

Elliot is a comprehensive recommendation framework that analyzes the recommendation problem from the researcher's perspective.

Diverse Image Captioning with Context-Object Split Latent Spaces (NeurIPS 2020)

Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones

CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"

PyTorch package for the discrete VAE used for DALL·E.

Machine learning, in numpy

Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow

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