Author: Deep Learner

Neural Network

Feature Learning in Infinite-Width Neural Networks

Empirical Experiments in “Feature Learning in Infinite-width Neural Networks” This repo contains code to replicate our experiments (Word2Vec, MAML) in our paper Feature Learning in Infinite-Width Neural NetworksGreg Yang, Edward Hu In short, the code here will allow you to train feature learning infinite-width neural networks on Word2Vec and on Omniglot (via MAML). Our results on Word2Vec: Our Results on MAML: Please see the README in individual folders for more details. This is the 4th paper in the Tensor Programs […]

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Automation

Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems

ACSC Automatic extrinsic calibration for non-repetitive scanning solid-state LiDAR and camera systems. System Architecture 1. Dependency Tested with Ubuntu 16.04 64-bit and Ubuntu 18.04 64-bit. ROS (tested with kinetic / melodic) Eigen 3.2.5 PCL 1.8 python 2.X / 3.X python-pcl opencv-python (>= 4.0) scipy scikit-learn transforms3d pyyaml mayavi (optional, for debug and visualization only) 2. Preparation 2.1 Download and installation Use the following commands to download this repo. Notice: the SUBMODULE should also be cloned. git clone –recurse-submodules https://github.com/HViktorTsoi/ACSC Compile […]

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Domain

Domain Consensus Clustering for Universal Domain Adaptation

Domain-Consensus-Clustering [CVPR2021] Domain Consensus Clustering for Universal Domain Adaptation Prerequisites To install requirements: pip install -r requirements.txt Python 3.6 GPU Memory: 10GB Pytorch 1.4.0 Getting Started Download the dataset: Office-31, OfficeHome, VisDA, DomainNet. Data Folder structure: Your dataset DIR: |-Office/domain_adaptation_images | |-amazon | |-webcam | |-dslr |-OfficeHome | |-Art | |-Product | |-… |-VisDA | |-train | |-validataion |-DomainNet | |-clipart | |-painting | |-… You need you modify the data_path in config files, i.e., config.root Training Train on one […]

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Neural Machine Translation (NMT), NMT Leave a comment

Machine Translation Weekly 87: Notes from ACL 2021

The story of the science fiction novel Roadside Picnic by Arkady and Boris Strugatsky (mostly known via Tarkovsky’s 1979 film Stalker) takes place after an extraterrestrial event called the Visitation. Some aliens stopped by, made a roadside picnic, and left behind plenty of weird and dangerous objects having features that contemporary science cannot explain. Although the UN tries to prevent people from entering the visitation zones before everything gets fully explored and explained, objects from the zone are traded on […]

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Advanced, CHATBOT, Data Science, NLP, Programming, Project, Python, Unstructured Data

Build an end-end Currency Convertor chatbot with Python and Dialogflow

This article was published as a part of the Data Science Blogathon Introduction Hello all, Hope you are fine. In this tutorial we will learn how to create chatbots using Dialogflow and python, as well we will learn the deployment of chatbots to telegram. In our previous articles, we have learned to create a simple rule-based chatbot using simple python and NLTK libraries. I would like to request you to have a look at the article creating a simple chatbot […]

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Transformer

Sign Language Transformers (CVPR’20)

Sign Language Transformers (CVPR’20) This repo contains the training and evaluation code for the paper Sign Language Transformers: Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation. This code is based on Joey NMT but modified to realize joint continuous sign language recognition and translation. For text-to-text translation experiments, you can use the original Joey NMT framework. Requirements Download the feature files using the data/download.sh script. [Optional] Create a conda or python virtual environment. Install required packages using the […]

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Self-Supervised

Self-Supervised Learning with Vision Transformers

Self-Supervised Learning with Vision Transformers By Zhenda Xie*, Yutong Lin*, Zhuliang Yao, Zheng Zhang, Qi Dai, Yue Cao and Han Hu This repo is the official implementation of “Self-Supervised Learning with Swin Transformers”. A important feature of this codebase is to include Swin Transformer as one of the backbones, such that we can evaluate the transferring performance of the learnt representations on down-stream tasks of object detection and semantic segmentation. This evaluation is usually not included in previous works due […]

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BERT

Using VideoBERT to tackle video prediction

VideoBERT This repo reproduces the results of VideoBERT (https://arxiv.org/pdf/1904.01766.pdf). Inspiration was taken from https://github.com/MDSKUL/MasterProject, but this repo tackles video prediction rather than captioning and masked language modeling. On a side note, since this model is extremely small, the results that are displayed here are extremely basic. Feel free to increase the model size per your computational resources and change the inference file to include temperature if necessary (As of now I have not implemented temperature). Here are all the steps […]

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Computer Vision

Multi-Task Vision and Language Representation Learning

12-in-1: Multi-Task Vision and Language Representation Learning Please cite the following if you use this code. Code and pre-trained models for 12-in-1: Multi-Task Vision and Language Representation Learning: @InProceedings{Lu_2020_CVPR, author = {Lu, Jiasen and Goswami, Vedanuj and Rohrbach, Marcus and Parikh, Devi and Lee, Stefan}, title = {12-in-1: Multi-Task Vision and Language Representation Learning}, booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2020} } and ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for […]

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