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BoltzmannEntropy /interviews.ai

Star4.6k

It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.

python data-science machine-learning deep-learning information-theory jobs pytorch autograd artificial-intelligence feature-extraction ensemble-learning logistic-regression convolutional-neural-networks bayesian-statistics loss-functions interview-preparation pytorch-tutorial graduate-school jax

UpdatedJan 21, 2022

bermanmaxim /LovaszSoftmax

Star1.4k

Code for the Lovász-Softmax loss (CVPR 2018)

pytorch neural-networks image-segmentation loss-functions

UpdatedApr 12, 2024
Jupyter Notebook

KaiyangZhou /pytorch-center-loss

Star982

Pytorch implementation of Center Loss

python computer-vision deep-learning pytorch feature-learning loss-functions center-loss

UpdatedFeb 19, 2023
Python

vandit15 /Class-balanced-loss-pytorch

Star792

Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"

computer-vision deep-learning pytorch loss-functions cvpr2019

UpdatedFeb 18, 2024
Python

csteinmetz1 /auraloss

Star771

Collection of audio-focused loss functions in PyTorch

audio pytorch loss-functions

UpdatedJul 30, 2024
Python

pbaylies /stylegan-encoder

Star745

StyleGAN Encoder - converts real images to latent space

deep-neural-networks deep-learning generative-adversarial-network gan neural-networks perceptual-losses loss-functions resnet-50

UpdatedDec 1, 2022
Jupyter Notebook

happynear /AMSoftmax

Star489

A simple yet effective loss function for face verification.

deep-learning face-recognition metric-learning loss-functions softmax

UpdatedAug 3, 2018
MATLAB

cvqluu /Angular-Penalty-Softmax-Losses-Pytorch

Star486

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

pytorch face-recognition metric-learning speaker-recognition embedding loss-functions face-verification sphereface normface fashion-mnist arcface am-softmax fmnist-dataset loss-function

UpdatedDec 13, 2023
Python

harleyszhang /dl_note

Star449

深度学习系统笔记，包含深度学习数学基础知识、神经网络基础部件详解、深度学习炼丹策略、模型压缩算法详解。

python machine-learning deep-learning cpp cnn pytorch convolutional-neural-networks loss-functions activation-functions inference-framework

UpdatedMar 11, 2025
Python

dingkeyan93 /DISTS

Star406

IQA: Deep Image Structure and Texture Similarity Metric

optimization structure texture pytorch similarity loss-functions quality-metrics iqa image-quality-assessment dists

UpdatedMay 22, 2020
Python

happynoom /DeepTrade

Star319

A LSTM model using Risk Estimation loss function for stock trades in market

deep-learning neural-network stock lstm lstm-model loss-functions stock-prediction lstm-networks

UpdatedAug 4, 2020
Python

GT-RIPL /L2C

Star314

Learning to Cluster. A deep clustering strategy.

deep-neural-networks deep-learning clustering artificial-intelligence supervised-learning semi-supervised-learning artificial-neural-networks transfer-learning unsupervised-learning loss-functions similarity-metric

UpdatedJan 8, 2020
Python

dingkeyan93 /IQA-optimization

Star311

Comparison of IQA models in Perceptual Optimization

optimization pytorch ssim loss-functions iqa image-quality-assessment vif steerable-filters lpips dists fsim

UpdatedAug 18, 2023
Python

kozistr /pytorch_optimizer

Star280

optimizer & lr scheduler & loss function collections in PyTorch

deep-learning sam optimizer pytorch ranger loss-functions lookahead nero adabound learning-rate-scheduling radam diffgrad gradient-centralization adamp adabelief madgrad adamd adan adai ademamix

UpdatedMar 24, 2025
Python

umbertogriffo /focal-loss-keras

Star279

Binary and Categorical Focal loss implementation in Keras.

deep-neural-networks deep-learning keras binary-classification loss-functions categorical-cross-entropy cross-entropy-loss

UpdatedDec 20, 2024
Python

NikolaZubic /2dimageto3dmodel

Star270

We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.