A multi-backend implementation of the Keras API, with support for TensorFlow, JAX, and PyTorch.

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

A library for optimization on Riemannian manifolds

Sionna: An Open-Source Library for Next-Generation Physical Layer Research

Monte Carlo tree search in JAX

Graph Neural Networks with Keras and Tensorflow 2.

Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning

Object detection using deep learning with Yolo, OpenCV and Python via Real Time Streaming Protocol (RTSP)

Skattning av peakdag och antal infekterade i covid-19-utbrottet i Stockholms län februari-april 2020.

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

A structured implementation of MuZero

BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling

Me testing our tensorflow and mnist in java

LVAE: Ladder Variational Auto-Encoders (NIPS 2016) with TensorFlow.

Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"

Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)

General Game Playing with Schema Networks

Reference implementation of a two-level RCN model

AlphaGo Zero Reimplementation. MCTS Self Play library.

Implementation of the variational continual learning method

Imagination Augmented Agents TensorFlow

Deep Variational Reinforcement Learning

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

World Models Experiments

Book PDF and simulation code for the monograph "Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency" by Emil Björnson, Jakob Hoydis and Luca Sanguinetti, published in Foundations and T…

Implementing Bayes by Backprop