mrsamsami / Convex-Optimization

Related projects: ⓘ

• zhd96 / ds-hdp-hmm
  Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model
  ☆23Updated 4 years ago
• sorooshafiee / WKF
  ☆14Updated 5 years ago
• mr-easy / GMM-EM-Python
  Python implementation of EM algorithm for GMM. And visualization for 2D case.
  ☆65Updated last year
• aidanscannell / mogpe
  Mixtures of Gaussian Process Experts in GPflow/TensorFlow
  ☆11Updated 2 years ago
• guxd / deepHMM
  A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]
  ☆53Updated last month
• GalaxyFox / DS-GA-3001-Deep_Kalman_Filter
  This is a re-implementation and test on paper Deep Kalman Filter: https://arxiv.org/pdf/1511.05121.pdf
  ☆15Updated 4 years ago
• AlexanderFabisch / gmr
  Gaussian Mixture Regression
  ☆168Updated 4 months ago
• Yusufma03 / pfrnns
  Particle Filter Recurrent Neural Networks (AAAI 2020)
  ☆74Updated last month
• fmorenopino / HeterogeneousHMM
  Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…
  ☆75Updated 10 months ago
• lubaroli / dust
  This is the code repository for the DuSt-MPC paper, published at Robotics: Science and Systems (RSS) 2021.
  ☆21Updated 3 years ago
• jamesross2 / Bayesian-HMM
  A non-parametric Bayesian approach to Hidden Markov Models
  ☆83Updated last year
• snowdj / CS228_PGM
  🌀 Stanford CS 228 - Probabilistic Graphical Models
  ☆65Updated 5 years ago
• adeveloperdiary / HiddenMarkovModel
  Code for the Hidden Markov Model Tutorial Series
  ☆82Updated 5 months ago
• Stanford-ILIAD / active-preference-based-gpr
  Companion code for RSS 2020 paper: "Active Preference-Based Gaussian Process Regression for Reward Learning"
  ☆39Updated 5 months ago
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆42Updated this week
• NoemieJaquier / GaBOtorch
  This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.
  ☆49Updated 2 years ago
• tianchenji / Multimodal-SVAE
  Multimodal Supervised Variational Autoencoder
  ☆16Updated 3 years ago
• fraenkel-lab / mogp
  Mixture of Gaussian Processes Model for Sparse Longitudinal Data
  ☆32Updated last year
• mishapadidar / GP-Derivatives-Variational-Inference
  ☆13Updated 2 years ago
• philipphennig / Probabilistic_ML
  Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023
  ☆122Updated last year
• paulbrodersen / entropy_estimators
  Estimators for the entropy and other information theoretic quantities of continuous distributions
  ☆130Updated 4 months ago
• dgedon / DeepSSM_SysID
  Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.
  ☆88Updated 2 years ago
• florist-notes / CS228_PGM
  🌲 Stanford CS 228 - Probabilistic Graphical Models
  ☆101Updated 3 weeks ago
• zhenxun-zhuang / SGDOL
  Implementation for "Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization"
  ☆9Updated 2 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆44Updated last year
• dheerajpatta / Coursera-1
  Quiz & Assignment of Coursera
  ☆13Updated 6 years ago
• jgosmann / goppy
  Gaussian Online Processes for Python
  ☆14Updated 6 months ago
• DanieleGammelli / DeepKalmanFilter
  Pyro/Pytorch implementation of Deep Kalman FIlter for shared-mobility demand prediction
  ☆42Updated 4 years ago
• grasool / Gaussian-Processes
  Introduction to Gaussian Processes
  ☆24Updated 6 years ago
• dn070017 / Variational-Autoencoders
  Beta-VAE, Conditional-VAE, Total Correlation-VAE, FactorVAE, Relevance Factor-VAE, Multi-Level VAE, (Soft)-IntroVAE (Beta-Version), LVAE,…
  ☆15Updated last year
• Bigpig4396 / Incremental-Gaussian-Process-Regression-IGPR
  ☆14Updated 2 years ago