This repository contains the code used for the implementation of the paper "Probabilistic Regression with HuberDistributions"

Last update: Dec 04, 2021

Overview

Public_prob_regression_with_huber_distributions

This repository contains the code used for the implementation of the paper "Probabilistic Regression with HuberDistributions"

Requirements:

conda (download from conda.io)
liblapack-dev (sudo apt-get install liblapack-dev)
blas
make
gcc

setup:

conda install environment.yaml

cd mathlib; make; cd ..

cd ImageTools; make; cd ..

How to use:

scripts folder contains all significant main files most important script is scripts/train.py run by $python -m scripts.train <CONFIG_FILE> --run_name example config files are in the folder configurations/ tensorflow logs and saved weights will be saved in the folder logs/

Owner

David Mohlin

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This repository contains the code used for the implementation of the paper "Probabilistic Regression with HuberDistributions"

Related tags

Overview

Public_prob_regression_with_huber_distributions

Requirements:

setup:

How to use:

Owner

David Mohlin

How the Deep Q-learning method works and discuss the new ideas that makes the algorithm work

IEGAN — Official PyTorch Implementation Independent Encoder for Deep Hierarchical Unsupervised Image-to-Image Translation

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Baseline inference Algorithm for the STOIC2021 challenge.

Example scripts for the detection of lanes using the ultra fast lane detection model in Tensorflow Lite.

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Official repository of DeMFI (arXiv.)

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