Python Guided-es-by-differentiable-simulators Resources

Differentiable Model Compression via Pseudo Quantization Noise DiffQ performs differentiable quantization using pseudo quantization noise. It can auto

GraphMask This repository contains an implementation of GraphMask, the interpretability technique for graph neural networks presented in our ICLR 2021

LED2-Net This is PyTorch implementation of our CVPR 2021 Oral paper "LED2-Net: Monocular 360˚ Layout Estimation via Differentiable Depth Rendering". Y

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer

xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely used in scientific computing applications as well as deep learning.

nvdiffmodeling Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Automatic 3D Model

DARTS-PT Code accompanying the paper ICLR'2021: Rethinking Architecture Selection in Differentiable NAS Ruochen Wang, Minhao Cheng, Xiangning Chen, Xi

gradsim gradSim: Differentiable simulation for system identification and visuomotor control gradSim is a unified differentiable rendering and multiphy

PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation Code repository for the paper: PoseAug: A Differentiable Pose Augme

GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Mo

ACMM [News] The code for ACMH is released!!! [News] The code for ACMP is released!!! About ACMM is a multi-scale geometric consistency guided multi-vi

Differentiable Optimizers with Perturbations in PyTorch This contains a PyTorch implementation of Differentiable Optimizers with Perturbations in Tens

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

PyTorch Implementation of Differentiable ODE Solvers This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpr

A Differentiable Recurrent Surface for Asynchronous Event-Based Data Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous

PG-MORL This repository contains the implementation for the paper Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Contro

Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021) An efficient PyTorch library for Point Cloud Completion.

Enjoy-Hamburger 🍔 Official implementation of Hamburger, Is Attention Better Than Matrix Decomposition? (ICLR 2021) Under construction. Introduction T

PENet: Precise and Efficient Depth Completion This repo is the PyTorch implementation of our paper to appear in ICRA2021 on "Towards Precise and Effic

UnsupervisedR&R: Unsupervised Pointcloud Registration via Differentiable Rendering This repository holds all the code and data for our recent work on

Differentiable molecular simulation of proteins with a coarse-grained potential This repository contains the learned potential, simulation scripts and

Note: We're moving to PyTorch Lightning! Read about the move here. From the end of February, torchbearer will no longer be actively maintained. We'll

CLIP-GLaSS Repository for the paper Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search An in-browser demo is

deluca Performant, differentiable reinforcement learning Notes This is pre-alpha software and is undergoing a number of core changes. Updates to follo

gtn_applications An applications library using GTN. Current examples include: Offline handwriting recognition Automatic speech recognition Installing

Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer