📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.

Last update: Jan 17, 2022

Overview

Weird Deep Learning Metrics

📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.

Metric	Description	Notes
Churn	Shows the disagreement between two model's prediction. Higher the churn, more the disagreement. Bounds: [0,1]. Takes two prediction arrays as inputs and retuns churn percentage.	From this paper

Owner

Rahul Vigneswaran

GitHub Repository

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

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[WACV21] Code for our paper: Samuel, Atzmon and Chechik, "From Generalized zero-shot learning to long-tail with class descriptors"

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This repository contains the code for the paper "PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization"

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Official Repository for our ICCV2021 paper: Continual Learning on Noisy Data Streams via Self-Purified Replay

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Official Repository for the paper "Improving Baselines in the Wild".

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Coarse implement of the paper "A Simultaneous Denoising and Dereverberation Framework with Target Decoupling", On DNS-2020 dataset, the DNSMOS of first stage is 3.42 and second stage is 3.47.

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📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.

Related tags

Overview

Weird Deep Learning Metrics

Owner

Rahul Vigneswaran

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Async API for controlling Hue Lights

Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"

ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプル

[WACV21] Code for our paper: Samuel, Atzmon and Chechik, "From Generalized zero-shot learning to long-tail with class descriptors"

Log4j JNDI inj. vuln scanner

FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset (CVPR2022)

Official PyTorch code for Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021)

This repository contains the code for the paper "PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization"

Implementing yolov4 target detection and tracking based on nao robot

Official Repository for our ICCV2021 paper: Continual Learning on Noisy Data Streams via Self-Purified Replay

Official Repository for the paper "Improving Baselines in the Wild".

This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,

A Simple Key-Value Data-store written in Python

SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

Coarse implement of the paper "A Simultaneous Denoising and Dereverberation Framework with Target Decoupling", On DNS-2020 dataset, the DNSMOS of first stage is 3.42 and second stage is 3.47.

A deep learning network built with TensorFlow and Keras to classify gender and estimate age.

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

Deep Learning Interviews book: Hundreds of fully solved job interview questions from a wide range of key topics in AI.

Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers