Python Reproducing-BowNet Resources

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Python Reproducing-BowNet Libraries

PyTorch framework, for reproducing experiments from the paper Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
PyTorch framework, for reproducing experiments from the paper Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu

Asaf 3 Dec 27, 2022
Reproducing-BowNet: Learning Representations by Predicting Bags of Visual Words

Reproducing-BowNet Our reproducibility effort based on the 2020 ML Reproducibility Challenge. We are reproducing the results of this CVPR 2020 paper:

null 6 Mar 16, 2022
Reproducing Results from A Hybrid Approach to Targeting Social Assistance

title author date output Reproducing Results from A Hybrid Approach to Targeting Social Assistance Lendie Follett and Heath Henderson 12/28/2021 html_

Lendie Follett 0 Jan 6, 2022
This repository contains unofficial code reproducing Agent57

Agent57 This repository contains unofficial code reproducing Agent57, which outp

null 19 Dec 29, 2022
Reproducing code of hair style replacement method from Barbershorp.

Barbershorp Reproducing code of hair style replacement method from Barbershorp. Also reproduces II2S, an improved version of Image2StyleGAN. Requireme

null 1 Dec 24, 2021
Reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer: Self-Attention with Linear Complexity)
Reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer: Self-Attention with Linear Complexity)

Linear Multihead Attention (Linformer) PyTorch Implementation of reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer:

Kui Xu 58 Dec 23, 2022
The repo for reproducing Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study

ECIR Reproducibility Paper: Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study This code corresponds to the reproducibility

ielab 3 Mar 31, 2022
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.

PySlowFast PySlowFast is an open source video understanding codebase from FAIR that provides state-of-the-art video classification models with efficie

Meta Research 5.3k Jan 3, 2023
Code for reproducing key results in the paper "InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets"

Status: Archive (code is provided as-is, no updates expected) InfoGAN Code for reproducing key results in the paper InfoGAN: Interpretable Representat

OpenAI 1k Dec 19, 2022
Code base for reproducing results of I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics. NeurIPS (2021)

Learning to Execute (L2E) Official code base for completely reproducing all results reported in I.Schubert, D.Driess, O.Oguz, and M.Toussaint: Learnin

null 3 May 18, 2022
Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining
Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining

LMSOC: An Approach for Socially Sensitive Pretraining Code for reproducing the paper LMSOC: An Approach for Socially Sensitive Pretraining to appear a

Twitter Research 11 Dec 20, 2022
Code for reproducing experiments in "Improved Training of Wasserstein GANs"

Improved Training of Wasserstein GANs Code for reproducing experiments in "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, Tensor

Ishaan Gulrajani 2.2k Jan 1, 2023
Using / reproducing ACD from the paper
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

Hierarchical neural-net interpretations (ACD) 🧠 Produces hierarchical interpretations for a single prediction made by a pytorch neural network. Offic

Chandan Singh 111 Jan 3, 2023
Pytorch implementation for reproducing StackGAN_v2 results in the paper StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
Pytorch implementation for reproducing StackGAN_v2 results in the paper StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

StackGAN-v2 StackGAN-v1: Tensorflow implementation StackGAN-v1: Pytorch implementation Inception score evaluation Pytorch implementation for reproduci

Han Zhang 809 Dec 16, 2022
Repository for reproducing `Model-Based Robust Deep Learning`

Model-Based Robust Deep Learning (MBRDL) In this repository, we include the code necessary for reproducing the code used in Model-Based Robust Deep Le

Alex Robey 16 Sep 19, 2022
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper

Deep Continuous Clustering Introduction This is a Pytorch implementation of the DCC algorithms presented in the following paper (paper): Sohil Atul Sh

Sohil Shah 197 Nov 29, 2022
Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

Image Crop Analysis This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this

Twitter Research 239 Jan 2, 2023