Max Kukuškin (max-kuk)

max-kuk

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Company:Leipzig University

Location:Leipzig

Home Page:max-kuk.github.io

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Max Kukuškin's starred repositories

actual

A local-first personal finance app

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k3-addons

Additional multi-backend functionality for Keras 3.

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SS-MAE

SS-MAE: Spatial-Spectral Masked Auto-Encoder for Mulit-Source Remote Sensing Image Classification (IEEE TGRS 2023)

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CAE

This is a PyTorch implementation of “Context AutoEncoder for Self-Supervised Representation Learning"

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multidim-positional-encoding

An implementation of 1D, 2D, and 3D positional encoding in Pytorch and TensorFlow

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SRL-SOA

Hyperspectral Band Selection using Self-Representation Learning with Sparse 1D-Operational Autoencoder (SRL-SOA)

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ContrastiveLearning

This repo demostrates how to use the concept of contrastive learning in an anommaly detection setting with autoencoders (also know as discriminative autoencoders)

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Deep-Chemometrics

Using deep learning approaches and convolutional neural networks (CNN) for spectroscopical data (deep chemometrics)

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normalizing-flows

Implementation of normalizing flows in TensorFlow 2 including a small tutorial.

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cs-flow

This is the official repository to the WACV 2022 paper "Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection" by Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn and Bastian Wandt.

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keras-visualizer

A Keras Model Visualizer

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scikeras

Scikit-Learn API wrapper for Keras.

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skorch

A scikit-learn compatible neural network library that wraps PyTorch

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FusAtNet-Dual-Attention-based-SpectroSpatial-Multimodal-Fusion-Network-for-Hyperspectral-and-LiDAR-

The repository contains relevant dataset and keras code for the paper, "FusAtNet: Dual Attention based SpectroSpatial Multimodal Fusion Network for Hyperspectral and LiDAR Classification"

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scikit-on-gRPC

Using Protocol Buffers and gRPC client-server communication to deploy a scikit-learn joblib exported model.

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tensorflow-serving-client

A prebuilt tensorflow serving client from the tensorflow serving proto files

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obsidian-permalink-opener

Obsidian plugin to open URLs based on a permalink or slug in the note properties. For use with Jekyll, Hugo, Eleventy, Astro, Obsidian Publish, and other publishing tools.

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MorphConvHyperNet

Inofficial code of MorphConvHyperNet ("Morphological Convolutional Neural Networks for Hyperspectral Image Classification")

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pipreqs

pipreqs - Generate pip requirements.txt file based on imports of any project. Looking for maintainers to move this project forward.

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keras-core

A multi-backend implementation of the Keras API, with support for TensorFlow, JAX, and PyTorch.

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segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

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keras_cv_attention_models

Keras beit,caformer,CMT,CoAtNet,convnext,davit,dino,efficientdet,edgenext,efficientformer,efficientnet,eva,fasternet,fastervit,fastvit,flexivit,gcvit,ghostnet,gpvit,hornet,hiera,iformer,inceptionnext,lcnet,levit,maxvit,mobilevit,moganet,nat,nfnets,pvt,swin,tinynet,tinyvit,uniformer,volo,vanillanet,yolor,yolov7,yolov8,yolox,gpt2,llama2, alias kecam

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pyod

A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

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alibi-detect

Algorithms for outlier, adversarial and drift detection

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lion-pytorch

🦁 Lion, new optimizer discovered by Google Brain using genetic algorithms that is purportedly better than Adam(w), in Pytorch

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battery

CLI for managing the battery charging status for M1 Macs

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lazypredict

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

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anomalib

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

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Hyper-DSNet

Source Code and Datasets for "A Deep-Shallow Fusion Network with Multi-Detail Extractor and Spectral Attention for Hyperspectral Pansharpening, IEEE J-STARS, 2022"

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