epfl-dlab Goto Github PK
Name: EPFL Data Science Lab (dlab)
Type: Organization
Location: Switzerland
Blog: dlab.epfl.ch
Name: EPFL Data Science Lab (dlab)
Type: Organization
Location: Switzerland
Blog: dlab.epfl.ch
Code and data for the WSDM '21 paper "Quotebank: A Corpus of Quotations from a Decade of News"
Scripts for cleaning and enriching Quotebank
The server to collect user data and learn an SVM in the SecVM project
Repository of data and code for the paper "Interventions for Softening Can Lead to Hardening of Opinions: Evidence from a Randomized Controlled Trial".
Repository of code and data for the paper "The effect of spokesperson attribution on public health message sharing during the COVID-19 pandemic".
Structuring Wikipedia Articles with Section Recommendations
symbol-lab is an environment for testing the models’ ability to encode input into a symbolic (discrete) compositional representation. With a structure that allows for fine-grained control over the difficulty of the task, and an arbitrary amount of training data, symbol-lab aids us in uncovering the strengths and weaknesses of existing methods and facilitates the development of new ones.
The data and the PyTorch implementation for the models and experiments in the paper "Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction".
Data and code for paper "Formation of Social Ties Influences Food Choice: A Campus-wide Longitudinal Study"
Fork of the "🤗 Transformers" repository. Extended to support the following decoding methods: MCTS, Stochastic Beam Search, Value-Guided Beam Search. Codebase extended on the understanding-decoding branch.
🤗 A specialized library for integrating context-free grammars (CFG) in EBNF with the Hugging Face Transformers
🤗 Transformers with Context-Free Grammar Generation Support
The data and the PyTorch implementation for the models and experiments in the paper "Language Model Decoding as Likelihood–Utility Alignment".
Demonstrate that installing and managing study add-ons works
Code and data for the AAAI'19 paper "Reverse-Engineering Satire, or 'Paper on Computational Humor Accepted Despite Making Serious Advances'"
A framework to clean the Wikipedia category network.
Repository for the article "When Sheep Shop: Measuring Herding Effects in Product Ratings with Natural Experiments" published at WWW2018
Wikipedia Image Classification project
Data and code for the paper "Sudden Attention Shifts on Wikipedia During the COVID-19 Crisis"
This is a repo containing all code and steps taken to download, setup the process and convert the whole English Wikipedia history from Wikitext to HTML format.
Source code for "Wikipedia Reader Navigation: When Synthetic Data is Enough"
Crosslingual Topic Modeling with WikiPDA
Quantifying Engagement with Citations on Wikipedia https://arxiv.org/abs/2001.08614
Code for the dataset paper: "YouNiverse: Large-Scale Channel and Video Metadata from English-Speaking YouTube"
YouTube channel embeddings and social dimensions
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.