Deep Learning

Implementation of Graph Transformer in Pytorch

Graph Transformer – Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by both Costa et al and Bakers lab for transforming MSA and pair-wise embedding into 3d coordinates. Todo add rotary embeddings for injecting adjacency information Install $ pip install graph-transformer-pytorch Usage import torch from graph_transformer_pytorch import GraphTransformer model = GraphTransformer( dim = 256, depth = 6, edge_dim = 512, # optional – if left out, edge dimensions is assumed to […]

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Bot

A chatbot made in RASA and helps the user to plan their vacation

rasa-travel-chatbot Here is my Senior Design Project that I implemented to graduate from Computer Engineering. It is a chatbot made in RASA and helps the user to plan their vacation in the Turkish language. In order to plan the user’s vacation, it provides reservations by asking various questions for hotel, flight, or event. Create a virtual environment of python 3.6 or greater. Navigate to the rasa directory. Run the command:rasa train After the model is trained, launch the rasa core […]

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Models

BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data

BoB This repository provides the implementation details for the ACL 2021 main conference paper: BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data. 1. Data Preparation In this work, we carried out persona-based dialogue generation experiments under a persona-dense scenario (English PersonaChat) and a persona-sparse scenario (Chinese PersonalDialog), with the assistance of a series of auxiliary inference datasets. Here we summarize the key information of these datasets and provide the links to download these datasets if […]

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ASCII Art

Convert any image into greyscale ASCII art in python

Image-to-ASCII Convert any image into greyscale ASCII art. Setup 1. Clone Repo git clonehttps://github.com/BSmith156/Image-to-ASCII.git 2. Install Requirements pip install -r requirements.txt Usage image_to_ascii.py input_file output_file [-i] [-max n] Arguments Argument Description input_file The image file being converted. output_file The file to store the ASCII art. -i Optional. Inverts the image colour, useful when displaying the output using a light font on a dark background. -max n Optional. Sets the maximum width/height of the output to n, 0 for no maximum. […]

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Natural Language Processing

Learning Dense Representations of Phrases at Scale

DensePhrases DensePhrases is an extractive phrase search tool based on your natural language inputs. From 5 million Wikipedia articles, it can search phrase-level answers to your questions or find related entities to (subject, relation) pairs in real-time. Due to the extractive nature of DensePhrases, it always provides an evidence passage for each phrase. Please see our paper Learning Dense Representations of Phrases at Scale (Lee et al., 2021) for more details. Installation # Install torch with conda (please check your […]

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Analysis

Hyperbolic Dimensionality Reduction via Horospherical Projections

HoroPCA This code is the official PyTorch implementation of the ICML 2021 paper: HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical ProjectionsInes Chami*, Albert Gu*, Dat Nguyen*, Christopher RéStanford UniversityPaper: https://arxiv.org/abs/2106.03306 Abstract. This paper studies Principal Component Analysis (PCA) for data lying in hyperbolic spaces. Given directions, PCA relies on: (1) a parameterization of subspaces spanned by these directions, (2) a method of projection onto subspaces that preserves information in these directions, and (3) an objective to optimize, namely the variance explained […]

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Graph

Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network

DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the journal Bioinformatics. DeepCDR is a hybrid graph convolutional network for cancer drug response prediction. It takes both multi-omics data of cancer cell lines and drug structure as inputs and predicts the drug sensitivity (binary or contineous IC50 value). Keras==2.1.4 TensorFlow==1.13.1 hickle >= 2.1.0 DeepCDR can be downloaded by git clone https://github.com/kimmo1019/DeepCDR Installation has been tested in […]

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Machine Learning

Flexible data structures for complex machine learning datasets

meerkat Meerkat provides fast and flexible data structures for working with complex machine learning datasets. Getting started pip install meerkat-ml Note: some parts of Meerkat rely on optional dependencies. If you know which optional dependencies you’d like to install, you can do so using something like pip install meerkat-ml[dev,text] instead. See setup.py for a full list of optional dependencies. Load your dataset into a DataPanel and get going! import meerkat as mk dp = mk.DataPanel.from_csv(“…”) What is Meerkat? Meerkat makes […]

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Machine Learning

3D Animal Reconstruction with Expectation Maximization in the Loop

Who Left the Dogs Out? Evaluation and demo code for our ECCV 2020 paper: Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop. Install Clone the repository with submodules: git clone –recurse-submoduleshttps://github.com/benjiebob/WLDO For segmentation decoding, install pycocotools python -m pip install “git+https://github.com/philferriere/cocoapi.git#subdirectory=PythonAPI” Datasets To use the StanfordExtra dataset, you will need to download the .json file via the repository. Please ensure you have StanfordExtra_v12 installed, which we released 1 Feb 2021. You may also wish […]

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Video

Implementation of FitVid video prediction model in JAX/Flax

FitVid Video Prediction Model Implementation of FitVid video prediction model in JAX/Flax. If you find this code useful, please cite it in your paper: @article{babaeizadeh2021fitvid, title={FitVid: Overfitting in Pixel-Level Video Prediction}, author= {Babaeizadeh, Mohammad and Saffar, Mohammad Taghi and Nair, Suraj and Levine, Sergey and Finn, Chelsea and Erhan, Dumitru}, journal={arXiv preprint arXiv:2106.13195}, year={2020} } Method FitVid is a new architecture for conditional variational video prediction. It has ~300 million parameters and can be trained with minimal training tricks. Sample […]

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