Convert python code to CUDA.
To convert a python file say named py_file.py to CUDA, run python generate_cuda.py --file py_file.py --arch {your_gpu_arch}, (if --arch is not specified, sm_61 will be used). Output will be saved in ./compiled.
Example run: python generate_cuda.py --file ./examples/test.py --arch sm_86
Bio-OFC gym implementation and Gym-Fly environment This repository includes the gym compatible implementation of the Bio-OFC algorithm from the paper
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Neograd This repo supports the paper Neograd: Gradient Descent with a Near-Ideal Learning Rate, which introduces the algorithm "Neograd". The paper an
Implementations of the algorithms in the paper Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters
This is the official PyTorch implementation of TMNet in the CVPR 2021 paper "Temporal Modulation Network for Controllable Space-Time VideoSuper-Resolu
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MIMIC-III Benchmarks Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database. Currently, the benchmark data
BADet: Boundary-Aware 3D Object Detection from Point Clouds (Pattern Recognition
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LegoNet This code is the implementation of ICML2019 paper LegoNet: Efficient Convolutional Neural Networks with Lego Filters Run python train.py You c
Installation: pip install -e . Installing DL2: First clone DL2 in a separate directory and install it using the following commands: git clone https:/
Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det
sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ
actions-includes Allows including an action inside another action (by preprocessing the Yaml file). Instead of using uses or run in your action step,
[AAAI 2021]DropLoss for Long-Tail Instance Segmentation [AAAI 2021] DropLoss for Long-Tail Instance Segmentation Ting-I Hsieh*, Esther Robb*, Hwann-Tz
Portfolio asset allocation strategies: from Markowitz to RNNs Research project to explore different approaches for optimal portfolio allocation starti
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