Alternatives and similar repositories for Duke-MLWS-2019

Users that are interested in Duke-MLWS-2019 are comparing it to the libraries listed below

• pymc-learn / pymc-learn-book
  Book: Practical Probabilistic Machine Learning in Python
  ☆10Updated 4 years ago
• stefanradev93 / cINN
  Contains legacy code and model examples for the paper "BayesFlow: Learning complex stochastic models with invertible neural networks"
  ☆23Updated 4 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• NicolasDurrande / Gaussian-Processes-short-course
  ☆14Updated 7 years ago
• steveli / gp-adapter
  Scalable GP Adapter for Time Series Classification
  ☆13Updated 7 years ago
• juliusberner / deep_kolmogorov
  Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)
  ☆22Updated 2 years ago
• ChicagoBoothML / ML2016
  BUS 41204: Machine Learning -- Winter 2016
  ☆11Updated 8 years ago
• snagcliffs / RKNN
  ☆20Updated 6 years ago
• zhulingchen / tfp-tutorial
  TensorFlow Probability Tutorial
  ☆37Updated 5 years ago
• duke-mlss / Duke-NLP-WS-2020
  Duke Natural Language Processing Winter School 2020
  ☆21Updated 5 years ago
• PhIMaL / DeePyMoD_tensorflow
  This implementation of DeePyMoD is no longer maintained! We switched to a PyTorch based implementation: https://github.com/PhIMaL/DeePyM…
  ☆24Updated 5 years ago
• ekochmar / cl-datasci-pnp
  Data Science: Principles and Practice, 2019-20
  ☆11Updated 5 years ago
• lawrennd / old_talks
  Talks from Neil Lawrence
  ☆54Updated last year
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 7 years ago
• matt-graham / phd-thesis
  Auxiliary variable Markov chain Monte Carlo methods
  ☆10Updated 7 years ago
• epfml / opt-shortcourse
  Short Course on Optimization for Machine Learning - Slides and Practical Lab - Pre-doc Summer School on Learning Systems, July 3 to 7, 20…
  ☆18Updated 7 years ago
• esdalmaijer / cluster_power
  Code and data for a simulation project aimed at computing statistical power for various dimensionality reduction and clustering algorithm…
  ☆13Updated 5 years ago
• fonnesbeck / gp_tutorial_pydata
  PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3
  ☆15Updated 7 years ago
• didriknielsen / ds3_abi_exercises
  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018
  ☆22Updated 6 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• Imperial-College-Data-Science-Society / workshops
  ☆19Updated 2 years ago
• QueensGambit / PGM-Causal-Reasoning
  Experiments on structure learning of Bayesian Networks with emphasis on finding causal relationship
  ☆9Updated 6 years ago
• namanUIUC / NonlinearComponentAnalysis
  Application of principal component analysis capturing non-linearity in the data using kernel approach
  ☆8Updated 6 years ago
• junhaobearxiong / Counterfactual-Prediction
  State space model + data pipeline to generate counterfactual time series trajectories on multiple clinical signals, used to evaluate the …
  ☆7Updated 6 years ago
• icme / cme258
  Libraries for Scientific Computing
  ☆10Updated 6 years ago
• dynamicslab / langevin-regression
  Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton
  ☆25Updated 3 years ago
• DmitryBorisenko / ensemble_tutorial
  ☆13Updated 4 years ago
• xinshi-chen / ParticleFlowBayesRule
  Pytorch implementation for "Particle Flow Bayes' Rule"
  ☆14Updated 5 years ago
• ritchieng / the-incredible-tensorflow
  The Incredible TensorFlow 2: a curated list of tutorials, papers, projects, communities and more relating to TensorFlow 2.
  ☆30Updated 5 years ago
• lightlightdyy / Deep-Learning-and-Causal-Inference
  ☆29Updated 6 years ago