shaabhishek

shaabhishek's Stars

• RomainLaroche/SPIBB

  Safe Policy Improvement with Baseline Bootstrapping

  Language:Python256

• dado93/pywearable

  Python package for extraction, visualization, and analysis of physiological data collected through wearable sensors.

  Language:Python51

• dtak/POPCORN-POMDP

  Implementation of "POPCORN: Partially Observed Prediction Constrained Reinforcement Learning" (Futoma, Hughes, Doshi-Velez, AISTATS 2020)

  Language:Python112

• google-deepmind/optax

  Optax is a gradient processing and optimization library for JAX.

  Language:Python1.6k176

• gehring/fax

  Language:Python789

• gehring/tilecoding

  A python implementation of tile coding using numpy.

  Language:Python113

• tsurumeso/pysparcl

  Python implementation of the sparse clustering methods

  Language:Python288

• SimiaoZuo/Transformer-Hawkes-Process

  Code for Transformer Hawkes Process, ICML 2020.

  Language:Python17448

• clinicalml/gumbel-max-scm

  Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)

  Language:Python4110

• dobriban/Topics-In-Modern-Statistical-Learning

  Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, calibration, etc

  15917

• maria-antoniak/little-mallet-wrapper

  A Python wrapper around the topic modeling functions of MALLET.

  Language:Jupyter Notebook9918

• josejimenezluna/pyGPGO

  Bayesian optimization for Python

  Language:Python24161

• jasonroy0/BNP-short-course

  Language:HTML147

• jluttine/tikz-bayesnet

  TikZ library for drawing Bayesian networks, graphical models and (directed) factor graphs in LaTeX.

  Language:TeX829147

• jameshensman/VFF

  Variational Fourier Features

  Language:Python8124

• jessicayung/machine-learning-flashcards

  Machine learning flashcards

  Language:TeX21542

• y0ast/deterministic-uncertainty-quantification

  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"

  Language:Python26731

• ksachdeva/rethinking-tensorflow-probability

  Statistical Rethinking (2nd Ed) with Tensorflow Probability

  Language:Jupyter Notebook26949

• rmcelreath/statrethinking_winter2019

  Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019

  2k392

• wohlert/semi-supervised-pytorch

  Implementations of various VAE-based semi-supervised and generative models in PyTorch

  Language:Python704123

• hurcy/awesome-ehr-deeplearning

  Curated list of awesome papers for electronic health records(EHR) mining, machine learning, and deep learning.

  41289

• MatthewDaws/PointProcesses

  Basics of point processes using python for simulation

  Language:Jupyter Notebook6014

• karpathy/pytorch-normalizing-flows

  Normalizing flows in PyTorch. Current intended use is education not production.

  Language:Jupyter Notebook83699

• bob-carpenter/ad-handbook

  Automatic Differentiation Handbook

  Language:C++14518

• chi-feng/mcmc-demo

  Interactive Markov-chain Monte Carlo Javascript demos

  Language:JavaScript778115

• rtqichen/torchdiffeq

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

  Language:Python5.5k908

• mattjj/autodidact

  A pedagogical implementation of Autograd

  Language:Jupyter Notebook942100

• mattjj/pybasicbayes

  Language:Python15360

• slinderman/recurrent-slds

  Recurrent Switching Linear Dynamical Systems

  Language:Python9423

• avehtari/BDA_course_Aalto

  Bayesian Data Analysis course at Aalto

  Language:TeX2.1k556