Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.
machine-learning
deep-learning
python
platform
research
finance
algorithmic-trading
auto-quant
fintech
investment
paper
quant
quant-dataset
quant-models
quantitative-finance
quantitative-trading
research-paper
stock-data
Обновлено 2024-09-12 18:44:27 +03:00
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
machine-learning
data-science
causal-inference
causality
treatment-effects
bayesian-networks
causal-machine-learning
causal-models
do-calculus
graphical-models
python3
Обновлено 2024-08-29 21:13:51 +03:00
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
machine-learning
python
deep-learning
pytorch
neural-architecture-search
deep-neural-networks
edge-computing
latency
inference
edge-ai
efficient-model
onnx-models
tensorflow-models
Обновлено 2024-07-31 00:16:53 +03:00
This tool helps automatic generation of grammatically valid synthetic Code-mixed data by utilizing linguistic theories such as Equivalence Constant Theory and Matrix Language Theory.
natural-language-processing
python3
code-switching
linguistics
synthetic-data-generation
code-mixing
data-generation
language-modeling
Обновлено 2024-07-31 00:01:52 +03:00
Graphormer is a general-purpose deep learning backbone for molecular modeling.
Обновлено 2024-05-28 09:22:34 +03:00
mapping flu incidence and modeling flu burden and transmission, focused on the Seattle Flu Study, public fork of https://github.com/seattleflu/incidence-mapper
Обновлено 2023-11-03 00:06:51 +03:00
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding (AAAI 2020) - PyTorch Implementation
Обновлено 2023-07-25 19:48:26 +03:00
Price analytics solution based on the double-machine-learning modeling approach
Обновлено 2023-06-27 15:48:52 +03:00
A suite of machine learning tools for modeling viral adaptation to host immune responses.
Обновлено 2023-06-14 18:17:59 +03:00
An R-powered custom visual implementing Autoregressive Integrated Moving Average (ARIMA) modeling for the forecasting. Time series forecasting is the use of a model to predict future values based on previously observed values.
Обновлено 2023-06-12 21:29:06 +03:00
Code for "Generative Code Modeling with Graphs" (ICLR'19)
Обновлено 2022-12-08 07:04:56 +03:00
Addin to open the SQL server management studio from within the modeling experience for Dynamics for Operations.
Обновлено 2022-11-28 22:12:20 +03:00
Microsoft Threat Modeling Template files
Обновлено 2022-11-28 22:12:03 +03:00
This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".
Обновлено 2022-09-29 18:17:40 +03:00
Deformed Implicit Field: Modeling 3D Shapes with Learned Dense Correspondence CVPR 2021
Обновлено 2022-07-04 06:30:54 +03:00
Compact .net tool aiding in sql data modeling.
Обновлено 2022-04-13 18:08:01 +03:00
The Azure Integration Migrator Model repo contains the source and target modeling entities along with template configuration and Liquid rendering functionality to populate the target model with AIS templates and assets.
Обновлено 2021-08-21 14:32:51 +03:00
IoT Simulation service
Обновлено 2021-01-26 02:45:41 +03:00
performance
performance-testing
dsl
haskell
model-checking
modeling
performance-analysis
performance-tuning
queueing-theory
Обновлено 2020-12-16 18:50:06 +03:00
Qubit Modeling Tools (QMT) for computational modeling of quantum devices
Обновлено 2019-06-19 00:56:29 +03:00
Scalable, fast, and lightweight system for large-scale topic modeling
Обновлено 2017-12-18 15:34:33 +03:00