Stars
code for the paper "Dynamic Correlation Clustering in Sublinear Update Time" accepted at ICML 2024
Open-source library for Graph Streaming. Solves the connected components problem using sub-linear space. Published in SIGMOD'22.
t-sne visualization of mnist images when feature is represented by raw pixels and cnn learned feature
Code for the paper "Equal Improvability: A New Fairness Notion Considering the Long-term Impact". Poster at ICLR 2023
collecting evidence on academic misconduct & it's time to change it!
Github Pages template based upon HTML and Markdown for personal, portfolio-based websites.
An efficient method for sampling from the Gram--Schmidt Walk Design.
Graph Neural Networks with Keras and Tensorflow 2.
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
Automatic extraction of relevant features from time series:
Percona TokuDB is a high-performance, write optimized, compressing, transactional storage engine for Percona Server. Issue tracker: https://tokutek.atlassian.net/browse/DB/ Wiki: https://github.com…
A repository of data on coronavirus cases and deaths in the U.S.
bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent
🎮 Advanced Deep Learning and Reinforcement Learning at UCL & DeepMind | YouTube videos 👉
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Modularized Implementation of Deep RL Algorithms in PyTorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Representation Learning on Graphs with Jumping Knowledge Networks
A MNIST-like fashion product database. Benchmark 👇
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable,…
Implemented Variational Autoencoder generative model in Keras for image generation and its latent space visualization on MNIST and CIFAR10 datasets
Interpretable neural spike train models with fully-Bayesian inference algorithms
Python module to compute the RESCAL tensor factorization
official implementation for the paper "Simplifying Graph Convolutional Networks"