99 Repositories
Python differentiable-nms Libraries
[ICLR 2022] Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics
CPDeform Code and data for paper Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics at ICLR 2022 (Spotlight). @InProceed
The official codes of our CVPR2022 paper: A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift
TwoStageAlign The official codes of our CVPR2022 paper: A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large Shift Pa
Point-NeRF: Point-based Neural Radiance Fields
Point-NeRF: Point-based Neural Radiance Fields Project Sites | Paper | Primary c
Differentiable Wavetable Synthesis
Differentiable Wavetable Synthesis
Differentiable Simulation of Soft Multi-body Systems
Differentiable Simulation of Soft Multi-body Systems Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming C. Lin [Paper] [Code] Updates The C++ backend s
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
DART Implementation for ICLR2022 paper Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. Environment [email protected] Use pi
This is the source code for the experiments related to the paper Unsupervised Audio Source Separation Using Differentiable Parametric Source Models
Unsupervised Audio Source Separation Using Differentiable Parametric Source Models This is the source code for the experiments related to the paper Un
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search DropNAS, a grouped operation dropout method for one-level DARTS, with better
Fast Differentiable Matrix Sqrt Root
Official Pytorch implementation of ICLR 22 paper Fast Differentiable Matrix Square Root
PyTorch implementation of Histogram Layers from DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation
deep-hist PyTorch implementation of Histogram Layers from DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation PyT
Relaxed-machines - explorations in neuro-symbolic differentiable interpreters
Relaxed Machines Explorations in neuro-symbolic differentiable interpreters. Baby steps: inc_stop Libraries JAX Haiku Optax Resources Chapter 3 (∂4: A
Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation.
SAFA: Structure Aware Face Animation (3DV2021) Official Pytorch Implementation of 3DV2021 paper: SAFA: Structure Aware Face Animation. Getting Started
High accurate tool for automatic faces detection with landmarks
faces_detanator High accurate tool for automatic faces detection with landmarks. The library is based on public detectors with high accuracy (TinaFace
Differentiable Annealed Importance Sampling (DAIS)
Differentiable Annealed Importance Sampling (DAIS) This repository contains the code to reproduce the DAIS results from the paper Differentiable Annea
Implicit neural differentiable FM synthesizer
Implicit neural differentiable FM synthesizer The purpose of this project is to emulate arbitrary sounds with FM synthesis, where the parameters of th
Nvdiffrast - Modular Primitives for High-Performance Differentiable Rendering
Nvdiffrast – Modular Primitives for High-Performance Differentiable Rendering Modular Primitives for High-Performance Differentiable Rendering Samuli
Differentiable Abundance Matching With Python
shamnet Differentiable Stellar Population Synthesis Installation You can install shamnet with pip. Installation dependencies are numpy, jax, corrfunc,
AlgoVision - A Framework for Differentiable Algorithms and Algorithmic Supervision
NeurIPS 2021 Paper "Learning with Algorithmic Supervision via Continuous Relaxations"
[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks
DiffMG This repository contains the code for our KDD 2021 Research Track paper: DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neura
Official PyTorch implementation of the ICRA 2021 paper: Adversarial Differentiable Data Augmentation for Autonomous Systems.
Adversarial Differentiable Data Augmentation This repository provides the official PyTorch implementation of the ICRA 2021 paper: Adversarial Differen
Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection
CP-Cluster Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection, Instance Segme
PennyLane is a cross-platform Python library for differentiable programming of quantum computers
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural ne
A library for differentiable nonlinear optimization.
Theseus A library for differentiable nonlinear optimization built on PyTorch to support constructing various problems in robotics and vision as end-to
torchbearer: A model fitting library for PyTorch
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
PiRank: Learning to Rank via Differentiable Sorting
PiRank: Learning to Rank via Differentiable Sorting This repository provides a reference implementation for learning PiRank-based models as described
Python tools for experimenting with differentiable intonation cost measures
Differentiable Intonation Tools The Differentiable Intonation Tools (dit) are a collection of Python functions to analyze the intonation in multitrack
Complete-IoU (CIoU) Loss and Cluster-NMS for Object Detection and Instance Segmentation (YOLACT)
Complete-IoU Loss and Cluster-NMS for Improving Object Detection and Instance Segmentation. Our paper is accepted by IEEE Transactions on Cybernetics
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
Taichi is a parallel programming language for high-performance numerical computations.
Taichi is a parallel programming language for high-performance numerical computations.
Learning infinite-resolution image processing with GAN and RL from unpaired image datasets, using a differentiable photo editing model.
Exposure: A White-Box Photo Post-Processing Framework ACM Transactions on Graphics (presented at SIGGRAPH 2018) Yuanming Hu1,2, Hao He1,2, Chenxi Xu1,
The repository forked from NVlabs uses our data. (Differentiable rasterization applied to 3D model simplification tasks)
nvdiffmodeling [origin_code] Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Autom
Fast, general, and tested differentiable structured prediction in PyTorch
Fast, general, and tested differentiable structured prediction in PyTorch
A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations
jaxdf - JAX-based Discretization Framework Overview | Example | Installation | Documentation ⚠️ This library is still in development. Breaking changes
A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation
A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation This repository contains the source code of the paper A Differentiable
A collection of differentiable SVD methods and also the official implementation of the ICCV21 paper "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"
Differentiable SVD Introduction This repository contains: The official Pytorch implementation of ICCV21 paper Why Approximate Matrix Square Root Outpe
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver
Shape As Points (SAP) Paper | Project Page | Short Video (6 min) | Long Video (12 min) This repository contains the implementation of the paper: Shape
Guiding evolutionary strategies by (inaccurate) differentiable robot simulators @ NeurIPS, 4th Robot Learning Workshop
Guiding Evolutionary Strategies by Differentiable Robot Simulators In recent years, Evolutionary Strategies were actively explored in robotic tasks fo
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language (NeurIPS 2021)
VRDP (NeurIPS 2021) Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language Mingyu Ding, Zhenfang Chen, Tao Du, Pin
Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)
DQC: Differentiable Quantum Chemistry Differentiable quantum chemistry package. Currently only support differentiable density functional theory (DFT)
an implementation of softmax splatting for differentiable forward warping using PyTorch
softmax-splatting This is a reference implementation of the softmax splatting operator, which has been proposed in Softmax Splatting for Video Frame I
Differentiable scientific computing library
xitorch: differentiable scientific computing library xitorch is a PyTorch-based library of differentiable functions and functionals that can be widely
DiSECt: Differentiable Simulator for Robotic Cutting
DiSECt: Differentiable Simulator for Robotic Cutting Website | Paper | Dataset | Video | Blog post DiSECt is a simulator for the cutting of deformable
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes This repository contains the source code accompanying the paper: FlexConv: C
ADOP: Approximate Differentiable One-Pixel Point Rendering
ADOP: Approximate Differentiable One-Pixel Point Rendering Abstract: We present a novel point-based, differentiable neural rendering pipeline for scen
Official Repo for ICCV2021 Paper: Learning to Regress Bodies from Images using Differentiable Semantic Rendering
[ICCV2021] Learning to Regress Bodies from Images using Differentiable Semantic Rendering Getting Started DSR has been implemented and tested on Ubunt
This project is used for the paper Differentiable Programming of Isometric Tensor Network
This project is used for the paper "Differentiable Programming of Isometric Tensor Network". (arXiv:2110.03898)
This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"
Differentiable Volumetric Rendering Paper | Supplementary | Spotlight Video | Blog Entry | Presentation | Interactive Slides | Project Page This repos
A PyTorch Library for Accelerating 3D Deep Learning Research
Kaolin: A Pytorch Library for Accelerating 3D Deep Learning Research Overview NVIDIA Kaolin library provides a PyTorch API for working with a variety
Official code release for ICCV 2021 paper SNARF: Differentiable Forward Skinning for Animating Non-rigid Neural Implicit Shapes.
Official code release for ICCV 2021 paper SNARF: Differentiable Forward Skinning for Animating Non-rigid Neural Implicit Shapes.
Differentiable architecture search for convolutional and recurrent networks
Differentiable Architecture Search Code accompanying the paper DARTS: Differentiable Architecture Search Hanxiao Liu, Karen Simonyan, Yiming Yang. arX
Differentiable Surface Triangulation
Differentiable Surface Triangulation This is our implementation of the paper Differentiable Surface Triangulation that enables optimization for any pe
OptNet: Differentiable Optimization as a Layer in Neural Networks
OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc
OptNet: Differentiable Optimization as a Layer in Neural Networks
OptNet: Differentiable Optimization as a Layer in Neural Networks This repository is by Brandon Amos and J. Zico Kolter and contains the PyTorch sourc
Pytorch implementation of DeepMind's differentiable neural computer paper.
DNC pytorch This is a Pytorch implementation of DeepMind's Differentiable Neural Computer (DNC) architecture introduced in their recent Nature paper:
Kornia is a open source differentiable computer vision library for PyTorch.
Open Source Differentiable Computer Vision Library
PennyLane is a cross-platform Python library for differentiable programming of quantum computers.
PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.
Json GUI for No Man's Sky save file
NMS-Save-Parser Json GUI for No Man's Sky save file GUI python NMS_SAVE_PARSER.py [optional|save.hg] converter only python convert.py usage: conver
Differentiable Factor Graph Optimization for Learning Smoothers @ IROS 2021
Differentiable Factor Graph Optimization for Learning Smoothers Overview Status Setup Datasets Training Evaluation Acknowledgements Overview Code rele
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom Sample on-line plotting while training(avg loss)/testing(writ
The official code for paper "R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling".
R2D2 This is the official code for paper titled "R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Mode
A Python library for differentiable optimal control on accelerators.
A Python library for differentiable optimal control on accelerators.
Code for our CVPR 2021 Paper "Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes".
Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes (CVPR 2021) Project page | Paper | Colab | Colab for Drawing App Rethinking Style
Differentiable Neural Computers, Sparse Access Memory and Sparse Differentiable Neural Computers, for Pytorch
Differentiable Neural Computers and family, for Pytorch Includes: Differentiable Neural Computers (DNC) Sparse Access Memory (SAM) Sparse Differentiab
Experiments with differentiable stacks and queues in PyTorch
Please use stacknn-core instead! StackNN This project implements differentiable stacks and queues in PyTorch. The data structures are implemented in s
[RSS 2021] An End-to-End Differentiable Framework for Contact-Aware Robot Design
DiffHand This repository contains the implementation for the paper An End-to-End Differentiable Framework for Contact-Aware Robot Design (RSS 2021). I
Hardware accelerated, batchable and differentiable optimizers in JAX.
JAXopt Installation | Examples | References Hardware accelerated (GPU/TPU), batchable and differentiable optimizers in JAX. Installation JAXopt can be
Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators
Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).
This is an differentiable pytorch implementation of SIFT patch descriptor.
This is an differentiable pytorch implementation of SIFT patch descriptor. It is very slow for describing one patch, but quite fast for batch. It can
EdMIPS: Rethinking Differentiable Search for Mixed-Precision Neural Networks
EdMIPS is an efficient algorithm to search the optimal mixed-precision neural network directly without proxy task on ImageNet given computation budgets. It can be applied to many popular network architectures, including ResNet, GoogLeNet, and Inception-V3.
Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators
Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).
PyTorch implementation of Soft-DTW: a Differentiable Loss Function for Time-Series in CUDA
Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch
A python implementation of differentiable quality diversity.
Differentiable Quality Diversity This repository is the official implementation of Differentiable Quality Diversity.
Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Parallel Tacotron2 Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Fast, differentiable sorting and ranking in PyTorch
Torchsort Fast, differentiable sorting and ranking in PyTorch. Pure PyTorch implementation of Fast Differentiable Sorting and Ranking (Blondel et al.)
Fast, general, and tested differentiable structured prediction in PyTorch
Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic
DiffQ performs differentiable quantization using pseudo quantization noise. It can automatically tune the number of bits used per weight or group of weights, in order to achieve a given trade-off between model size and accuracy.
Differentiable Model Compression via Pseudo Quantization Noise DiffQ performs differentiable quantization using pseudo quantization noise. It can auto
Official implementation of GraphMask as presented in our paper Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking.
GraphMask This repository contains an implementation of GraphMask, the interpretability technique for graph neural networks presented in our ICLR 2021
CVPR 2021 Oral paper "LED2-Net: Monocular 360˚ Layout Estimation via Differentiable Depth Rendering" official PyTorch implementation.
LED2-Net This is PyTorch implementation of our CVPR 2021 Oral paper "LED2-Net: Monocular 360˚ Layout Estimation via Differentiable Depth Rendering". Y
Open Source Differentiable Computer Vision Library for PyTorch
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer
xitorch: differentiable scientific computing library
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.
Differentiable rasterization applied to 3D model simplification tasks
nvdiffmodeling Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Automatic 3D Model
[ICLR2021oral] Rethinking Architecture Selection in Differentiable NAS
DARTS-PT Code accompanying the paper ICLR'2021: Rethinking Architecture Selection in Differentiable NAS Ruochen Wang, Minhao Cheng, Xiangning Chen, Xi
Differentiable simulation for system identification and visuomotor control
gradsim gradSim: Differentiable simulation for system identification and visuomotor control gradSim is a unified differentiable rendering and multiphy
Repository for the paper "PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation", CVPR 2021.
PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation Code repository for the paper: PoseAug: A Differentiable Pose Augme
Official PyTorch Code of GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection (CVPR 2021)
GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Mo
Differentiable Optimizers with Perturbations in Pytorch
Differentiable Optimizers with Perturbations in PyTorch This contains a PyTorch implementation of Differentiable Optimizers with Perturbations in Tens
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie
Fast, general, and tested differentiable structured prediction in PyTorch
Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
PyTorch Implementation of Differentiable ODE Solvers This library provides ordinary differential equation (ODE) solvers implemented in PyTorch. Backpr
Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous Event-Based Data"
A Differentiable Recurrent Surface for Asynchronous Event-Based Data Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021)
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021) An efficient PyTorch library for Point Cloud Completion.
[ICLR 2021] Is Attention Better Than Matrix Decomposition?
Enjoy-Hamburger 🍔 Official implementation of Hamburger, Is Attention Better Than Matrix Decomposition? (ICLR 2021) Under construction. Introduction T
UnsupervisedR&R: Unsupervised Pointcloud Registration via Differentiable Rendering
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
Differentiable molecular simulation of proteins with a coarse-grained potential This repository contains the learned potential, simulation scripts and
torchbearer: A model fitting library for PyTorch
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
Performant, differentiable reinforcement learning
deluca Performant, differentiable reinforcement learning Notes This is pre-alpha software and is undergoing a number of core changes. Updates to follo
Code for ACM MM 2020 paper "NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination"
NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination The offical implementation for the "NOH-NMS: Improving Pedestrian Detection by
Applications using the GTN library and code to reproduce experiments in "Differentiable Weighted Finite-State Transducers"
gtn_applications An applications library using GTN. Current examples include: Offline handwriting recognition Automatic speech recognition Installing
Open Source Differentiable Computer Vision Library for PyTorch
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer