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tattler-telegram's Projects

alzheimersiq icon alzheimersiq

Repository hosting deep learning podcasts about Alzheimers Disease.

baselines icon baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

blocksparse icon blocksparse

Efficient GPU kernels for block-sparse matrix multiplication and convolution

gym icon gym

A toolkit for developing and comparing reinforcement learning algorithms.

gym3 icon gym3

Vectorized interface for reinforcement learning environments

homepage icon homepage

Custom Start/home page (multi LIVE search) with live animated weather and news ticker - written in HTML/JS. Minimal, self-hosted, and dope.

infogan icon infogan

Code for reproducing key results in the paper "InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets"

jquery-bootstrap icon jquery-bootstrap

Responsive jQuery News Ticker Plugin with Bootstrap 4 - Bootstrap News Box

jquery-easy-ticker icon jquery-easy-ticker

jQuery easy ticker is a news ticker like plugin, which scrolls the list infinitely. It is highly customizable, flexible with lot of features and works in all browsers.

mujoco-py icon mujoco-py

MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.

news icon news

:newspaper: RSS/Atom feed reader

news-1 icon news-1

Tattler Telegram News (Progress Web App Template)

python icon python

All Algorithms implemented in Python

pytorch icon pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

qrack icon qrack

Comprehensive, GPU accelerated framework for developing universal virtual quantum processors

spinningup icon spinningup

An educational resource to help anyone learn deep reinforcement learning.

ticker-tape icon ticker-tape

A Python library that aggregates news from various sources and publishes them to a rolling ticker tape.

vdvae icon vdvae

Repository for the paper "Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images"

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