Toolbox of analysis for the related paper. /!\ In progress
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Updated
May 10, 2020 - Jupyter Notebook
Toolbox of analysis for the related paper. /!\ In progress
Deep Metric Learning
A simple 3-layer fully connected network performing the density ratio estimation using the loss for log-likelihood ratio estimation (LLLR).
Design of a CNN (Convolutional Neural Networks) to classify CIFAR-10 images
Angular triplet center loss implementation in Pytorch.
performing linear regression
PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA
Stock Trend Prediction App: In these project I created stock trend web application to predicted continuous real time trend of desired stock input taken from user with fetching data from "Yahoo Finance".
Generating a TensorFlow model that predicts values in a sinewave
Inverse Supervised Learning
Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation
Official PyTorch implementation for "PROPEL: Probabilistic Parametric Regression Loss for Convolutional Neural Networks"
Seach Losses of our paper 'Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search', accepted by ICLR 2021.
Tensorflow Implementation of Focal Frequency Loss for Image Reconstruction and Synthesis [ICCV 2021]
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis
Core components of neural networks An introduction to Keras Setting up a deep-learning workstation Using neural networks to solve basic classification and regression problems
📄 Official implementation regarding the paper "Programmatically Evolving Losses in Machine Learning".
A new loss proposed that are sensitive towards image corruption and high information to noise trade off
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