Conditional Gradients For The Approximately Vanishing Ideal

Related tags

Deep Learningcgavi
Overview

Conditional Gradients For The Approximately Vanishing Ideal

Code for the paper:

Wirth, E., and Pokutta, S. (2022). Conditional Gradients for the Approximately Vanishing Ideal. To Appear in Proceedings of AISTATS.

Installation guide

Download the repository and store it in your preferred location, say ~/tmp.

Open your terminal and navigate to ~/tmp.

Run the command:

$ conda env create --file environment.yml

This will create the conda environment approximately_vanishing_ideal.

Activate the conda environment with:

$ conda activate approximately_vanishing_ideal

In the file global_.py, change the value of gpu_memory_ to the maximum amount of gpu you wish to use to perform computations.

Run the tests:

>>> python3 -m unittest

No errors should occur.

Execute the experiments:

>>> python3 experiments.py

This will create a folder named data_frames, which continues subfolders containing the experiment results.

The experiments can be displayed as latex_code by executing:

>>> experiments_results.py
You might also like...
Code for paper "Document-Level Argument Extraction by Conditional Generation". NAACL 21'

Argument Extraction by Generation Code for paper "Document-Level Argument Extraction by Conditional Generation". NAACL 21' Dependencies pytorch=1.6 tr

VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech Jaehyeon Kim, Jungil Kong, and Juhee Son In our rece

A denoising diffusion probabilistic model (DDPM) tailored for conditional generation of protein distograms
A denoising diffusion probabilistic model (DDPM) tailored for conditional generation of protein distograms

Denoising Diffusion Probabilistic Model for Proteins Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to gen

This repository holds the code for the paper "Deep Conditional Gaussian Mixture Model forConstrained Clustering".

Deep Conditional Gaussian Mixture Model for Constrained Clustering. This repository holds the code for the paper Deep Conditional Gaussian Mixture Mod

Official implementation of the paper DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows
Official implementation of the paper DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows

DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows Official implementation of the paper DeFlow: Learning Complex Im

 CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution This is the official implementation code of the paper "CondLaneNe

Cancer metastasis detection with neural conditional random field (NCRF)
Cancer metastasis detection with neural conditional random field (NCRF)

NCRF Prerequisites Data Whole slide images Annotations Patch images Model Training Testing Tissue mask Probability map Tumor localization FROC evaluat

Synthesizing and manipulating 2048x1024 images with conditional GANs
Synthesizing and manipulating 2048x1024 images with conditional GANs

pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio

 Official implementation of the ICCV 2021 paper
Official implementation of the ICCV 2021 paper "Conditional DETR for Fast Training Convergence".

The DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergence, and present a conditional cross-attention mechanism for fast DETR training. Our approach is motivated by that the cross-attention in DETR relies highly on the content embeddings and that the spatial embeddings make minor contributions, increasing the need for high-quality content embeddings and thus increasing the training difficulty.

Releases(v2.0.0)
Owner
IOL Lab @ ZIB
IOL Lab @ ZIB
Subnet Replacement Attack: Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks

Subnet Replacement Attack: Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks Official implementation of paper Towards Practic

Xiangyu Qi 8 Dec 30, 2022
Oscar and VinVL

Oscar: Object-Semantics Aligned Pre-training for Vision-and-Language Tasks VinVL: Revisiting Visual Representations in Vision-Language Models Updates

Microsoft 938 Dec 26, 2022
Datasets for new state-of-the-art challenge in disentanglement learning

High resolution disentanglement datasets This repository contains the Falcor3D and Isaac3D datasets, which present a state-of-the-art challenge for co

NVIDIA Research Projects 37 May 26, 2022
The Most Efficient Temporal Difference Learning Framework for 2048

moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar

Hung Guei 5 Nov 23, 2022
Code for paper "Multi-level Disentanglement Graph Neural Network"

Multi-level Disentanglement Graph Neural Network (MD-GNN) This is a PyTorch implementation of the MD-GNN, and the code includes the following modules:

Lirong Wu 6 Dec 29, 2022
Activity image-based video retrieval

Cross-modal-retrieval Our approach is focus on Activity Image-to-Video Retrieval (AIVR) task. The compared methods are state-of-the-art single modalit

BCMI 75 Oct 21, 2021
Code of Puregaze: Purifying gaze feature for generalizable gaze estimation, AAAI 2022.

PureGaze: Purifying Gaze Feature for Generalizable Gaze Estimation Description Our work is accpeted by AAAI 2022. Picture: We propose a domain-general

39 Dec 05, 2022
WatermarkRemoval-WDNet-WACV2021

WatermarkRemoval-WDNet-WACV2021 Thank you for your attention. Citation Please cite the related works in your publications if it helps your research: @

LUYI 63 Dec 05, 2022
VD-BERT: A Unified Vision and Dialog Transformer with BERT

VD-BERT: A Unified Vision and Dialog Transformer with BERT PyTorch Code for the following paper at EMNLP2020: Title: VD-BERT: A Unified Vision and Dia

Salesforce 44 Nov 01, 2022
Official implementation for the paper: Multi-label Classification with Partial Annotations using Class-aware Selective Loss

Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel

99 Dec 27, 2022
Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021.

Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021. Bobo Xi, Jiaojiao Li, Yunsong Li and Qian Du. Code f

Bobo Xi 7 Nov 03, 2022
RDA: Robust Domain Adaptation via Fourier Adversarial Attacking

RDA: Robust Domain Adaptation via Fourier Adversarial Attacking Updates 08/2021: check out our domain adaptation for video segmentation paper Domain A

17 Nov 30, 2022
Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022)

Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022) Introdu

anonymous 14 Oct 27, 2022
Koç University deep learning framework.

Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU

1.4k Dec 31, 2022
Pytorch Lightning code guideline for conferences

Deep learning project seed Use this seed to start new deep learning / ML projects. Built in setup.py Built in requirements Examples with MNIST Badges

Pytorch Lightning 1k Jan 06, 2023
Datasets, Transforms and Models specific to Computer Vision

vision Datasets, Transforms and Models specific to Computer Vision Installation First install the nightly version of OneFlow python3 -m pip install on

OneFlow 68 Dec 07, 2022
Code for EmBERT, a transformer model for embodied, language-guided visual task completion.

Code for EmBERT, a transformer model for embodied, language-guided visual task completion.

41 Jan 03, 2023
implementation for paper "ShelfNet for fast semantic segmentation"

ShelfNet-lightweight for paper (ShelfNet for fast semantic segmentation) This repo contains implementation of ShelfNet-lightweight models for real-tim

Juntang Zhuang 252 Sep 16, 2022
A stable algorithm for GAN training

DRAGAN (Deep Regret Analytic Generative Adversarial Networks) Link to our paper - https://arxiv.org/abs/1705.07215 Pytorch implementation (thanks!) -

195 Oct 10, 2022
This repository includes code of my study about Asynchronous in Frequency domain of GAN images.

Exploring the Asynchronous of the Frequency Spectra of GAN-generated Facial Images Binh M. Le & Simon S. Woo, "Exploring the Asynchronous of the Frequ

4 Aug 06, 2022