weicao1990

weicao1990's Stars

• Lightning-AI/pytorch-lightning

  Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

  Language:Python28k2477.1k3.3k

• microsoft/qlib

  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.

  Language:Python15.2k2969052.6k

• interpretml/interpret

  Fit interpretable models. Explain blackbox machine learning.

  Language:C++6.2k144441726

• rtqichen/torchdiffeq

  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

  Language:Python5.5k125216908

• FASTSHIFT/X-TRACK

  A GPS bicycle speedometer that supports offline maps and track recording

  Language:C5.4k91831.2k

• guofei9987/scikit-opt

  Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)

  Language:Python5.2k47176985

• babyname/fate

  Fate is a modern science chinese name create tool.

  Language:Go2.3k6292459

• thuml/Autoformer

  About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

  Language:Jupyter Notebook1.9k15205410

• yandex-research/rtdl

  Research on Tabular Deep Learning: Papers & Packages

  Language:Python869352597

• zhihanyue/ts2vec

  A universal time series representation learning framework

  Language:Python588642142

• microsoft/FOST

  FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.

  Language:Python25891445

• jxx123/simglucose

  A Type-1 Diabetes simulator implemented in Python for Reinforcement Learning purpose

  Language:Python2321742111

• callmefeifei/baby-names

  看程序员奶爸是如何通过代码给宝宝起名的?

  Language:Python22041855

• xchuwenbo/realseries

  RealSeries is a comprehensive out-of-the-box Python toolkit for various tasks, including Anomaly Detection, Granger causality and Forecast with Uncertainty, of dealing with Time Series Datasets.

  Language:Jupyter Notebook21201

• braisCB/E2E-FS

  E2E-FS: An End-to-End Feature Selection Method for Neural Networks

  Language:Python11314

• vanderschaarlab/Hybrid-ODE-NeurIPS-2021

  Code for Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression (NeurIPS 2021)

  Language:Jupyter Notebook2103

• weicao1990/TabSurvey

  Experiments on Tabular Data Models

  Language:Python1100