Deep Learning

Python Feature Engineering Cookbook, published by Packt

deepinterpolation is a Python library to denoise data by removing independent noise. Importantly training does NOT require ground truth

LA-MCTS is a new MCTS based derivative-free meta-solver. Compared to Bayesian optimization, and evolutionary algorithm, it learns to partition the search space, thereby 🌟 finding a better solution with fewer samples.

This repositorie is created for anyone who wants to do research about 3D detection in automanous scence. We will update the lateset papers as soon as possible.

[PyTorch] Implementation of CVPR'20 oral paper - D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features

Here's a web-based application built to allow an user to upload an image of a handwritten digit or draw them in the app itself and get a prediction by the model as to what he/she has entered.

This is the official pytorch implementation for paper: IF-Defense: 3D Adversarial Point Cloud Defense via Implicit Function based Restoration

Pytorch implementation for reproducing AttnGAN results in the paper AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

D2Det using mmdetection v2.1, supporting Objects365 and LVIS

SMAC: Learning Selective Mutual Attention and Contrast for RGB-D Saliency Detection

PyTSMod is a open-source library for Time-Scale Modification algorithms in Python 3. PyTSMod contains basic TSM algorithms such as Overlap-Add (OLA), Waveform-Similarity Overlap-Add (WSOLA), Time-Domain Pitch-Synchronous Overlap-A

FastAPI Skeleton App to serve machine learning models production-ready.

tract is a Neural Network inference toolkit. It can read Tensorflow 1, ONNX or NNEF, optimize them and run data through them.

A GUI for Nvidia's GauGAN/SPADE like shown in the tech demo.

SMARTS (Scalable Multi-Agent RL Training School) is a simulaton platform for reinforcement learning and multi-agent research on autonomous driving. Its focus is on realistic and diverse interactions. It is part of the XingTian sui

It is a project that conducts a study on predicting the cross section of Chinese stock market returns with a large panel of 75 individual firm characteristics and also uses “big-data” econometric methods.

OpenBCT is a Non Official Reimplementation for Towards Backward-Compatible Representation Learning (CVPR 2020 oral), which aims at achieving compatibility across different models.

Implementation of Memformer, a Memory-augmented Transformer, in Pytorch. It includes memory slots, which are updated with attention, learned efficiently through Memory-Replay BackPropagation (MRBP) through time. The other contribu

Codebase for arXiv preprint "NeRF++: Analyzing and Improving Neural Radiance Fields"

This is the code for our paper ``Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach''.

Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

AITrack is a 6-Degree of Freedom headtracker designed to work alongside Opentrack for its use in simulators/games.

Framework for the reproducible classification of Alzheimer's disease using deep learning

A curated list of awesome research papers, projects, code, dataset, workshops etc. related to virtual try-on.

MedICaT is a dataset of medical images, captions, subfigure-subcaption annotations, and inline textual references. Instructions for access are provided here.

tldrstory is a framework for AI-powered understanding of headlines and text content related to stories. tldrstory applies zero-shot labeling over text, which allows dynamically categorizing content. This framework also builds a tx

This is a simple and efficient differentiable rasterization-based renderer which has been used in several GVV publications. The implementation is free of most third-party libraries such as OpenGL. The core implementation is in CUD

Material of the MICCAI 2020 tutorial on weakly supervised learning for semantic segmentation

Implementation of the EMNLP 2020 paper "Counterfactual Generator: A Weakly-Supervised Method for Named Entity Recognition".

The Fusion 360 Gallery Dataset contains rich 2D and 3D geometry data derived from parametric CAD models. The dataset is produced from designs submitted by users of the CAD package Autodesk Fusion 360 to the Autodesk Online Gallery

A docker based low-latency deep learning library and inference server written in C++11 using the PyTorch C++ frontend.

NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture Search, Hyperparameter Tuning and Model Compression.