Session-aware Item-combination Recommendation with Transformer Network
2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1
-
- The code corresponding to the best submission (0.39224) is here.
Session-aware Item-combination Recommendation with Transformer Network
Overview
A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2
3.2k Dec 30, 2022
This is an official implementation of the CVPR2022 paper "Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots".
Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots Blind2Unblind Citing Blind2Unblind @inproceedings{wang2022blind2unblind, tit
58 Dec 06, 2022
Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.
Example scripts for the detection of lanes using the ultra fast lane detection model in ONNX.
35 Sep 07, 2022
一个免费开源一键搭建的通用验证码识别平台，大部分常见的中英数验证码识别都没啥问题。
captcha_server 一个免费开源一键搭建的通用验证码识别平台，大部分常见的中英数验证码识别都没啥问题。 使用方法 python = 3.8 以上环境 pip install -r requirements.txt -i https://pypi.douban.com/simple gun
189 Dec 02, 2022
BMN: Boundary-Matching Network
BMN: Boundary-Matching Network A pytorch-version implementation codes of paper: "BMN: Boundary-Matching Network for Temporal Action Proposal Generatio
260 Dec 06, 2022
Mall-Customers-Segmentation - Customer Segmentation Using K-Means Clustering
Overview Customer Segmentation is one the most important applications of unsupervised learning. Using clustering techniques, companies can identify th
2 Jan 03, 2022
State-to-Distribution (STD) Model
State-to-Distribution (STD) Model In this repository we provide exemplary code on how to construct and evaluate a state-to-distribution (STD) model fo
[email protected]">
2 Apr 07, 2022
Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models.
Statutory Interpretation Data Set This repository contains the data set created for the following research papers: Savelka, Jaromir, and Kevin D. Ashl
17 Dec 23, 2022
Image-Scaling Attacks and Defenses
Image-Scaling Attacks & Defenses This repository belongs to our publication: Erwin Quiring, David Klein, Daniel Arp, Martin Johns and Konrad Rieck. Ad
163 Nov 21, 2022
This repo is to be freely used by ML devs to check the GAN performances without coding from scratch.
GANs for Fun Created because I can! GOAL The goal of this repo is to be freely used by ML devs to check the GAN performances without coding from scrat
13 Jan 26, 2022
A crash course in six episodes for software developers who want to become machine learning practitioners.
Featured code sample tensorflow-planespotting Code from the Google Cloud NEXT 2018 session "Tensorflow, deep learning and modern convnets, without a P
2.6k Jan 08, 2023
Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO)
V-MPO Simple code to demonstrate Deep Reinforcement Learning by using an on-policy adaptation of Maximum a Posteriori Policy Optimization (MPO) in Pyt
9 Jun 06, 2022
Implementation of the method proposed in the paper "Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation"
Neural Descriptor Fields (NDF) PyTorch implementation for training continuous 3D neural fields to represent dense correspondence across objects, and u
167 Jan 06, 2023
Management Dashboard for Torchserve
Torchserve Dashboard Torchserve Dashboard using Streamlit Related blog post Usage Additional Requirement: torchserve (recommended:v0.5.2) Simply run:
103 Dec 10, 2022
Checking fibonacci - Generating the Fibonacci sequence is a classic recursive problem
Fibonaaci Series Generating the Fibonacci sequence is a classic recursive proble
1 Feb 15, 2022
Repo for "TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets" at [email protected]
TableParser Repo for "TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets" at
Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021)
Towards the D-Optimal Online Experiment Design for Recommender Selection (KDD 2021) Contact
PyJokes - Joking around with Python library pyjokes
Hi, it's Muhaimin again 👋 This is something unorthodox but cool. Don't forget t
1 Feb 02, 2022
On the model-based stochastic value gradient for continuous reinforcement learning
On the model-based stochastic value gradient for continuous reinforcement learning This repository is by Brandon Amos, Samuel Stanton, Denis Yarats, a
46 Dec 15, 2022
Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)
Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets This is the official PyTorch implementation for the paper Rapid Neural A
48 Dec 26, 2022