Deep Learning

QuarkDet lightweight object detection in PyTorch .Real-Time Object Detection on Mobile Devices.

This is the official PyTorch package for the discrete VAE used for DALL·E.

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises incl

DF21 is an implementation of Deep Forest 2021.2.1

Code and files to go along with CS329s machine learning model deployment tutorial.

RLStructures is a library to facilitate the implementation of new reinforcement learning algorithms. It includes a library, a tutorial, and different RL algorithms provided as examples.

Code for Langer et al. "Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks", IROS, 2020.

Deep Graph Library(DGL)은 기존의 DL 프레임워크(e.g. PyTorch, MXNet, Gluon 등)위에 그래프 뉴럴 네트워크 모델을 간편하게 구현하기 위한 Python 패키지입니다. DGL은 아키텍쳐 디자인 상에서 NetworkX의 API와 패러다임을 따르고 지향하고 있습니다.

TIGER is a Python toolbox to conduct graph vulnerability and robustness research. TIGER contains numerous state-of-the-art methods to help users conduct graph vulnerability and robustness analysis on graph structured data.

ProbNumDiffEq.jl provides probabilistic ODE solvers for the DifferentialEquations.jl ecosystem.

A Flax (Linen) implementation of ResNet (He, Kaiming, et al. 2015), ResNet-D (He, Tong et al. 2020), and ResNest (Zhang, Hang et al. 2020). The code is modular so you can mix and match the various stem, residual, and bottleneck im

Metatheory.jl is a general purpose metaprogramming and algebraic computation library for the Julia programming language, designed to take advantage of the powerful reflection capabilities to bridge the gap between symbolic mathema

Experiments on unsupervised point cloud reconstruction.

ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds

Pre-trained NFNets with 99% of the accuracy of the official paper "High-Performance Large-Scale Image Recognition Without Normalization".

The official implementation of "Puzzle-CAM: Improved localization via matching partial and full features".

This repository contains the source code of our ACL 2020 paper Screenplay Summarization Using Latent Narrative Structure.

Learning Cascaded Convolutional Networks for Blind Single Image Super-Resolution

Official implementation of the paper Image Generators with Conditionally-Independent Pixel Synthesis

The official implementation of the Molecule Attention Transformer.

This library contains JAX and Pytorch implementations of neural ODEs and Bayesian layers for stochastic variational inference. A rudimentary JAX implementation of differentiable SDE solvers is also provided, refer to torchsde [2]

Lambda Networks from the paper LambdaNetworks: Modeling Long-Range Interactions Without Attention by Bello et al. Adds support for Rank 3 and Rank 5 tensor inputs as well as initial implementation of ResNet-D with Lambda Convoluti

Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping

This repository provides a minimal implementation of adaptive gradient clipping (AGC) (as proposed in High-Performance Large-Scale Image Recognition Without Normalization1) in TensorFlow 2. The paper attributes AGC as a crucial co

ICPC Sinchon 2021 Winter Algorithm Camp 고급반에서 진행한 강의의 강의 노트들입니다.

Official code to reproduce the results and data presented in the paper Contrastive Learning Inverts the Data Generating Process.

Official PyTorch implementation of "Joint Object Detection and Multi-Object Tracking with Graph Neural Networks"

[arXiv 2021] Instance Localization for Self-supervised Detection Pretraining

Concept Whitening for Interpretable Image Recognition

LIDIA: Lightweight Learned Image Denoising with Instance Adaptation (NTIRE, 2020)

Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms.

📴 OffCon^3: SOTA PyTorch SAC and TD3 Implementations

This repository provides code and data to train and evaluate a weakly supervised method for rigid 3D scene flow estimation.