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benchmark_results

visual tracker benchmark results

bioconda-recipes

Conda recipes for the bioconda channel.

caser_pytorch

A PyTorch implementation of Convolutional Sequence Embedding Recommendation Model (Caser)

cfrbm

CFRBM is a implementation of the RBM model to the collaborative filtering task

clair3-mp

collaborative-denoising-auto-encoder

Collaborative Denoising Auto-Encoder for Top-N Recommender Systems (CDAE)

dancenet

DanceNet -💃💃Dance generator using Autoencoder, LSTM and Mixture Density Network. (Keras)

dasiamrpn

Distractor-aware Siamese Networks for Visual Object Tracking (ECCV2018)

dca

Deep count autoencoder for denoising scRNA-seq data

dcfnet

DCFNet: Discriminant Correlation Filters Network for Visual Tracking

deepvariant

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

dssm

ecnano

A target captured medical exome ONT sequencing with amplicon variant calling workflow

goturn_matconvnet

A matlab re-implementation of GOTURN

medaka

Sequence correction provided by ONT Research

meta_trackers

neural_collaborative_filtering

Neural Collaborative Filtering

py-mdnet

MDNet python implementation

pyspark-tutorial

PySpark-Tutorial provides basic algorithms using PySpark

recommendersystem-paper

This repository includes some papers that I have read or which I think may be very interesting.

siamfc-tf

State-of-the-art object tracking at high framerates, in TensorFlow.

spark-movie-lens

An on-line movie recommender using Spark, Python Flask, and the MovieLens dataset

surprise

A Python scikit for building and analyzing recommender systems

tbcf

Tracking Benchmark for Correlation Filters

tracker_benchmark

vital_release

VITAL: VIsual Tracking via Adversarial Learning

vot-toolkit

Visual Object Tracking (VOT) challenge evaluation toolkit

whatshap

Read-based phasing of genomic variants, also called haplotype assembly

youtube-recommendation-tensorflow

code of paper `Deep Neural Networks for Youtube Recommendation`

zhengzhenxian.github.io

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