Bayesian inference with probabilistic programming.

Welcome to the Physics-based Deep Learning Book v0.3 - the GenAI Edition

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

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

Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.

Machine Learning library for the web and Node.

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

[ICASSP 2024] This is the official code for "VoiceFlow: Efficient Text-to-Speech with Rectified Flow Matching"

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"

GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation [IJCV2023]

Simulate realistic trajectory data seen through sporadic reporting

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

Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

Materials of the Nordic Probabilistic AI School 2019.

Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python

Multi-Touch Attribution

A repository for generative models

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

Materials of the Nordic Probabilistic AI School 2021.

A library for discrete-time Markov chains analysis.

State-of-the-art neural cardinality estimators for join queries

Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference

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]

A machine learning library for spacecraft collision avoidance

A Python Library for Deep Probabilistic Modeling

Variational Inference in Gaussian Mixture Model