probabilistic-models

Bayesian inference with probabilistic programming.

Code for modelling estimated deaths and cases for COVID19.

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai

Machine Learning library for the web and Node.

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, etc.)

Implementation of WaveGrad high-fidelity vocoder from Google Brain in PyTorch.

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

Sample code for the Model-Based Machine Learning book.

Collection of probabilistic models and inference algorithms

Unofficial Pytorch code for "Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models"

Materials of the Nordic Probabilistic AI School 2019.

Simulate realistic trajectory data seen through sporadic reporting

A repository for generative models

Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

Visual Inertial Odometry (VIO) / Simultaneous Localization & Mapping (SLAM) using iSAM2 framework from the GTSAM library.

Training an n-gram based Language Model using KenLM toolkit for Deep Speech 2

Materials of the Nordic Probabilistic AI School 2021.

Multi-Touch Attribution

PyTorch implementation of the paper "NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity." (NeurIPS 2020)

Code for ICML 2019 paper "Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering" [long-oral]