AdriBena's starred repositories
spinningup
An educational resource to help anyone learn deep reinforcement learning.
pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
OpenNMT-py
Open Source Neural Machine Translation and (Large) Language Models in PyTorch
torchdiffeq
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
tensorspace
Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js
practical-pytorch
Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained
flownet2-pytorch
Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
pytorch-kaldi
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
pointer-generator
Code for the ACL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks"
pytorch-openai-transformer-lm
🐥A PyTorch implementation of OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI
3d-pose-baseline
A simple baseline for 3d human pose estimation in tensorflow. Presented at ICCV 17.
medicaldetectiontoolkit
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
FlowNetPytorch
Pytorch implementation of FlowNet by Dosovitskiy et al.
cnn-dailymail
Code to obtain the CNN / Daily Mail dataset (non-anonymized) for summarization
flownet2-tf
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Quantitative-Big-Imaging-2018
(Latest semester at https://github.com/kmader/Quantitative-Big-Imaging-2019) The material for the Quantitative Big Imaging course at ETHZ for the Spring Semester 2018
jlsca-tutorials
Tutorials and examples on how to use Jlsca, the high-performance side channel analysis toolkit written in Julia
Curiosity_Driven_Goal_Exploration
Code to reproduce the results of "Curiosity Driven Exploration of Learned Disentangled Goal Spaces"