Conditional Gradients For The Approximately Vanishing Ideal

Last update: May 25, 2022

Related tags

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

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

87 Dec 26, 2022

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

1.7k Jan 8, 2023

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

108 Nov 23, 2022

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

17 Oct 30, 2022

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

86 Nov 16, 2022

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

311 Dec 30, 2022

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

731 Jan 1, 2023

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

6k Dec 27, 2022

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.

281 Dec 30, 2022

Conditional Gradients For The Approximately Vanishing Ideal

Related tags

Overview

Conditional Gradients For The Approximately Vanishing Ideal

Installation guide

You might also like...

Code for paper "Document-Level Argument Extraction by Conditional Generation". NAACL 21'

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

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

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

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

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

Cancer metastasis detection with neural conditional random field (NCRF)

Synthesizing and manipulating 2048x1024 images with conditional GANs

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

Releases(v2.0.0)

v2.0.0(Sep 12, 2022)

v1.0.0(Jan 31, 2022)

Owner

IOL Lab @ ZIB

JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation

Official implementation of the ICLR 2021 paper

OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

Pytorch implementation of the paper Time-series Generative Adversarial Networks

Ladder Variational Autoencoders (LVAE) in PyTorch

An open-source, low-cost, image-based weed detection device for fallow scenarios.

PyTorch implementation of "A Two-Stage End-to-End System for Speech-in-Noise Hearing Aid Processing"

MoCoPnet - Deformable 3D Convolution for Video Super-Resolution

keyframes-CNN-RNN(action recognition)

[NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data

Code for NAACL 2021 full paper "Efficient Attentions for Long Document Summarization"

unet for image segmentation

Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs

Docker containers of baseline agents for the Crafter environment

Part-aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking

Complex-Valued Neural Networks (CVNN)Complex-Valued Neural Networks (CVNN)

[ECE NTUA] 👁 Computer Vision - Lab Projects & Theoretical Problem Sets (2020-2021)

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity

Simple object detection app with streamlit

Python scripts for performing 3D human pose estimation using the Mobile Human Pose model in ONNX.