To set up the environment, use the provided scripts in the docker/ folder to build and run the codebase inside a docker container.
Use
./docker/build.sh
to build the container and
./docker/run.sh
to launch a docker container.
Then run lsvae/train_lsvae.py to start training.
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SinIR (Official Implementation) Requirements To install requirements: pip install -r requirements.txt We used Python 3.7.4 and f-strings which are in
TensorLy_Quantum TensorLy-Quantum is a Python library for Tensor-Based Quantum Machine Learning that builds on top of TensorLy and PyTorch. Website: h
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks Under construction. Description Code for Phase diagram of S
Obs-Causal-Q-Network AAAI 2022 - Training a Resilient Q-Network against Observational Interference Preprint | Slides | Colab Demo | Environment Setup
Overview This is a set of simple scripts to process the Imagenet-1K dataset as TFRecords and make index files for NVIDIA DALI. Make TFRecords To run t
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
CyGNet This repository reproduces the AAAI'21 paper “Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Network
Lingvo is a framework for building neural networks in Tensorflow, particularly sequence models.
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