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

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Deep Learningcomputer-visiondeep-learningmetricsdnnpytorchcomparisonpytorch-implementation
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
Rahul Vigneswaran
GitHub Repository
Use tensorflow to implement a Deep Neural Network for real time lane detection

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A fast and easy to use, moddable, Python based Minecraft server!

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This code is 3d-CNN model that can predict environmental value

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ArtEmis: Affective Language for Art

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Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

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328 Dec 30, 2022
Meta Language-Specific Layers in Multilingual Language Models

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Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme (NeurIPS2021)

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Shaojie Li 34 Mar 31, 2022
WaveFake: A Data Set to Facilitate Audio DeepFake Detection

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Blender Python - Node-based multi-line text and image flowchart

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The PyTorch implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision.

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A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

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Meta Learning for Semi-Supervised Few-Shot Classification

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Automatic meme generation model using Tensorflow Keras.

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PyTorch implementations of the paper: "Learning Independent Instance Maps for Crowd Localization"

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Unsupervised Learning of Video Representations using LSTMs

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This is a library for training and applying sparse fine-tunings with torch and transformers.

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