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Name: BlueMatrix
Type: User
Name: BlueMatrix
Type: User
Performance analysis of predictive (alpha) stock factors
Pytorch implementation of Augmented Neural ODEs :sunflower:
AutoGluon: AutoML for Image, Text, and Tabular Data
A curated list of resources on implicit neural representations.
Drawing Bayesian networks, graphical models, and technical frameworks in LaTeX.
Python Backtesting library for trading strategies
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace and more
Predicting market price of an agricultural product (arecanut) using Bayesian time series methods
Bayesian nonparametric spectral estimation
TensorFlow code and pre-trained models for BERT
Scalable, event-driven, deep-learning-friendly backtesting library
Chess reinforcement learning by AlphaGo Zero methods.
Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."
PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, DGR, DGR+distill, RtF, iCaRL).
[CVPR 2022 Oral] Crafting Better Contrastive Views for Siamese Representation Learning
Code for "Deep Convolutional Networks as shallow Gaussian Processes"
Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching
Public facing notes page
DataCamp data-science courses
Official pytorch implementation of the paper "Deep Kernel Transfer in Gaussian Processes for Few-shot Learning"
Deep Probabilistic Koopman: long-term time-series forecasting under quasi-periodic uncertainty
Deep convolutional gaussian processes.
This jupyter notebook is used to demonstrate our recent work, "DeepLOB: Deep Convolutional Neural Networks for Limit Order Books", published in IEEE Transactions on Singal Processing. We use FI-2010 dataset and present how model architecture is constructed here. The FI-2010 is publicly avilable and interested readers can check out their paper.
Implementation of stochastic variational inference for differentially deep gaussian processes
A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch
disentanglement_lib is an open-source library for research on learning disentangled representations.
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.