October 3, 2021 Algorithms

A compilation of important Data Structures and Algorithms based on Python

This repository is a compilation of important Data Structures and Algorithms based on Python. Please make seperate folders for different topics😇 The following topics will be elaborated: Big O Time Complexity Tuples Dictionaries Lists Arrays Looping Sorting Algorithms Bubble Sort Selection Sort Insertion Sort Bucket Sort Merge Sort Quick Sort Heap Sort Tree Sort Shell Sort Count Sort Radix Sort Searching Algorithms Linear Search Binary Search Backtracking Dynamic Programming Linked List Singly Linked List Doubly Linked List Circular Singly Linked […]

October 3, 2021 hacktoberfest

Adding codes of data structures and algorithms, leetCode, hackerrank etc solutions in different languages

This repository is for adding codes of data structures and algorithms, leetCode, hackerrank etc solutions in different languages Go through the Contributing Guidelines for a detailed information on contributing to this repository! For beginners – Jump to this section. PRs made without adding any useful Resource / Code / Solving Issues will be marked as invalid/spam. If this is your first time creating a Pull Request – go through the next section to know how to create one. If you […]

October 3, 2021 Deep Learning

A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation

We strongly believe in open and reproducible deep learning research. Our goal is to implement an open-source medical image segmentation library of state of the art 3D deep neural networks in PyTorch. We also implemented a bunch of data loaders of the most common medical image datasets. This project started as an MSc Thesis and is currently under further development. Although this work was initially focused on 3D multi-modal brain MRI segmentation we are slowly adding

October 3, 2021 Sequences

ULMFiT for Genomic Sequence Data

This is an implementation of ULMFiT for genomics classification using Pytorch and Fastai. The model architecture used is based on the AWD-LSTM model, consisting of an embedding, three LSTM layers, and a final set of linear layers. The ULMFiT approach uses three training phases to produce a classification model: Train a language model on a large, unlabeled corpus Fine tune the language model on the classification corpus Use the fine tuned language model to initialize a classification model This method […]

October 3, 2021 Dataset

TorchXRayVision: A library of chest X-ray datasets and models

A library for chest X-ray datasets and models. Including pre-trained models. ( 🎬promo video about the project) Motivation: While there are many publications focusing on the prediction of radiological and clinical findings from chest X-ray images much of this work is inaccessible to other researchers. In the case of researchers addressing clinical questions it is a waste of time for them to train models from scratch. To address this, TorchXRayVision provides pre-trained models which are trained on large cohorts of […]

October 3, 2021 Deep Learning

A PyTorch Library for Accelerating 3D Deep Learning Research

Overview NVIDIA Kaolin library provides a PyTorch API for working with a variety of 3D representations and includes a growing collection of GPU-optimized operations such as modular differentiable rendering, fast conversions between representations, data loading, 3D checkpoints and more. Kaolin library is part of a larger suite of tools for 3D deep learning research. For example, the Omniverse Kaolin App will allow interactive visualization of 3D checkpoints. To find out more about the Kaolin ecosystem, visit the NVIDIA Kaolin Dev […]

October 3, 2021 Structure

Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks

This repository contains the code used for word-level language model and unsupervised parsing experiments in Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks paper, originally forked from the LSTM and QRNN Language Model Toolkit for PyTorch. If you use this code or our results in your research, we’d appreciate if you cite our paper as following: @article{shen2018ordered, title={Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks}, author={Shen, Yikang and Tan, Shawn and Sordoni, Alessandro and Courville, Aaron}, journal={arXiv preprint […]

October 3, 2021 PyTorch

LSTM and QRNN Language Model Toolkit for PyTorch

This repository contains the code used for two Salesforce Research papers: The model comes with instructions to train: word level language models over the Penn Treebank (PTB), WikiText-2 (WT2), and WikiText-103 (WT103) datasets character level language models over the Penn Treebank (PTBC) and Hutter Prize dataset (enwik8) The model can be composed of an LSTM or a Quasi-Recurrent Neural Network (QRNN) which is two or more times faster than the cuDNN LSTM in this setup while achieving equivalent or better […]

October 3, 2021 PyTorch

A PyTorch implementation of Attentive Recurrent Comparators

PyTorch implementation of Attentive Recurrent Comparators by Shyam et al. A blog explaining Attentive Recurrent Comparators Visualizing Attention On Same characters On Different Characters How to run? Download data A one-time 52MB download. Shouldn’t take more than a few minutes. Train Let it train until the accuracy rises to at least 80%. Early stopping is not implemented yet. You will have to manually kill the process.

October 3, 2021 Neural Network

Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling

Pytorch implementation of “Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling” (https://arxiv.org/pdf/1609.01454.pdf) Intent prediction and slot filling are performed in two branches based on Encoder-Decoder model. dataset (Atis) You can get data from here Requirements Train python3 train.py –data_path ‘your data path e.g. ./data/atis-2.train.w-intent.iob’ Result GitHub https://github.com/DSKSD/RNN-for-Joint-NLU

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