Alternatives and similar repositories for ST210A

Users that are interested in ST210A are comparing it to the libraries listed below

• KuNyaa / berkeleydeeprlcourse-homework-pytorch-solution
  Solutions for CS294-112 Fall2018 assignments in Pytorch
  ☆20Updated 7 years ago
• debmandal / RL-Causality
  References at the Intersection of Causality and Reinforcement Learning
  ☆89Updated 5 years ago
• kushagra06 / CS228_PGM
  🌀 Stanford CS 228 - Probabilistic Graphical Models
  ☆122Updated 6 years ago
• inf16nyu / home
  ☆78Updated 8 years ago
• mlss-2019 / slides
  ☆260Updated 6 years ago
• sa3305 / rl
  An advanced course on reinforcement learning offered at Columbia University IEOR in Spring 2018
  ☆62Updated 5 years ago
• mlss-2019 / tutorials
  ☆276Updated 5 years ago
• silencial / DeepRL
  Berkeley CS285 2019 homework solution
  ☆31Updated 2 years ago
• talwarabhimanyu / my-solutions-The-Elements-of-Statistical-Learning
  My solutions to problems of The Elements of Statistical Learning by Profs. Hastie, Tibshirani, and Friedman.
  ☆90Updated 6 years ago
• kjytay / stanford-stats
  My notes from class
  ☆74Updated 7 years ago
• ee227c / ee227c.github.io
  EE227C (Spring 2018) Course page
  ☆225Updated 4 years ago
• KuNyaa / berkeleydeeprlcourse-homework-pytorch
  Assignments for CS294-112 Fall2018 in Pytorch
  ☆64Updated 7 years ago
• cicl-stanford / csm
  Contains all materials for the paper "A counterfactual simulation model of causal judgment".
  ☆24Updated 4 years ago
• google-deepmind / mc_gradients
  ☆170Updated last year
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆93Updated 3 years ago
• ks838 / Murphy-Machine-Learning-A-Probabilistic-Perspective-Errata-and-Notes-4th-printing
  Murphy's Machine Learning: A Probabilistic Perspective Errata (4th and later printings)
  ☆68Updated 5 years ago
• dimenwarper / awesome-bayes
  List of resources for bayesian inference
  ☆157Updated 6 years ago
• tengyuma / cs229m_notes
  ☆236Updated 2 years ago
• rmgarnett / cse515t
  Materials for Bayesian Methods in Machine Learning Course
  ☆90Updated this week
• dobriban / Topics-in-deep-learning
  Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)
  ☆95Updated 2 years ago
• otokonoko8 / deep-Bayesian-nonparametrics-papers
  The collection of papers about combining deep learning and Bayesian nonparametrics
  ☆121Updated 5 years ago
• maxwshen / iap-cidl
  Causal Inference & Deep Learning, MIT IAP 2018
  ☆89Updated 7 years ago
• joanbruna / ir18
  Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18
  ☆68Updated 6 years ago
• zixu1986 / Doubly_Stochastic_Gradients
  Code for doubly stochastic gradients
  ☆25Updated 10 years ago
• joanbruna / MathsDL-spring19
  Mathematics of Deep Learning, Courant Insititute, Spring 19
  ☆278Updated 6 years ago
• tuananhle7 / aesmc
  Library for Auto-Encoding Sequential Monte Carlo
  ☆18Updated last year
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆45Updated 2 years ago
• damaru2 / ntk
  NTK reading group
  ☆87Updated 5 years ago
• PierreBoyeau / decision-making-vaes
  ☆19Updated 3 years ago
• fwcore / mean-field-theory-deep-learning
  paper lists and information on mean-field theory of deep learning
  ☆78Updated 6 years ago