Python Adaptive-gradient-clipping Resources

2s-AGCN Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19 Note PyTorch version should be 0.3! For PyTor

MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes

InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De

Geometrically Adaptive Dictionary Attack on Face Recognition This is the Pytorch code of our paper "Geometrically Adaptive Dictionary Attack on Face R

BiMix The code for Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation arxiv Framework: visualization results: Requiremen

Adaptive Class Suppression Loss for Long-Tail Object Detection This repo is the official implementation for CVPR 2021 paper: Adaptive Class Suppressio

Text Summarization models if you are able to endorse me on Arxiv, i would be more than glad https://arxiv.org/auth/endorse?x=FRBB89 thanks This repo i

PAML PyTorch implementation of the paper: "Preference-Adaptive Meta-Learning for Cold-Start Recommendation", IJCAI, 2021. (Continuously updating ) Int

SeqGAN Requirements: Tensorflow r1.0.1 Python 2.7 CUDA 7.5+ (For GPU) Introduction Apply Generative Adversarial Nets to generating sequences of discre

py-earth A Python implementation of Jerome Friedman's Multivariate Adaptive Regression Splines algorithm, in the style of scikit-learn. The py-earth p

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa

Stochastic Model Building (SMB) This repository includes a new fast and robust stochastic optimization algorithm for training deep learning models. Th

A distributed, plug-n-play algorithm for multi-robot applications with a priori non-computable objective functions Kapoutsis, A.C., Chatzichristofis,

SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning We propose a SASE mode

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig

Nevergrad - A gradient-free optimization platform nevergrad is a Python 3.6+ library. It can be installed with: pip install nevergrad More installati

CircuitPython_XAC_Gamepad Setup process Install CircuitPython 7 or above in your board. Add the init.py file under \lib\adafruit_hid directory of CIRC

Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems This is our experimental code for RecSys 2021 paper "Learning

catsim - Computerized Adaptive Testing Simulator Quick start catsim is a computerized adaptive testing simulator written in Python 3.4 (with modificat

AdaConv Unofficial PyTorch implementation of the Adaptive Convolution architecture for image style transfer from "Adaptive Convolutions for Structure-

Greedy Gradient Ensemble for De-biased VQA Code release for "Greedy Gradient Ensemble for Robust Visual Question Answering" (ICCV 2021, Oral). GGE can

TextBPN Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection； Accepted by ICCV2021. Note: The complete code (including training and t

Intermediate Domain Module (IDM) This repository is the official implementation for IDM: An Intermediate Domain Module for Domain Adaptive Person Re-I

snn-localization repo PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch. Install Dependencies Orig

OSCAR Project Page | Paper This repository contains the codebase used in OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Ma

Introduction This script trains an agent with stochastic policy gradient ascent to solve the Lunar Lander challenge from OpenAI. In order to run this

Implicit Deep Adaptive Design (iDAD) This code supports the NeurIPS paper 'Implicit Deep Adaptive Design: Policy-Based Experimental Design without Lik

Generalized Data Weighting via Class-level Gradient Manipulation This repository is the official implementation of Generalized Data Weighting via Clas

ATS About Source code of the paper Meta-learning with an Adaptive Task Scheduler. If you find this repository useful in your research, please cite the

Generalized Data Weighting via Class-level Gradient Manipulation This repository is the official implementation of Generalized Data Weighting via Clas

AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsampling Abstract Pooling layers are essential building blocks of Convolutional Ne

PonderNet-TensorFlow This is an Unofficial Implementation of the paper: PonderNet: Learning to Ponder in TensorFlow. Official PyTorch Implementation:

Gradient CLI Get started: Create Account • Install CLI • Tutorials • Docs Resources: Website • Blog • Support • Contact Sales Gradient is an an end-to

Gradient representations in ReLU networks as similarity functions by Dániel Rácz and Bálint Daróczy. This repo contains the python code related to our

CARMS: Categorical-Antithetic-REINFORCE Multi-Sample Gradient Estimator This is the official code repository for NeurIPS 2021 paper: CARMS: Categorica

1. SaWDE.m is the main function 2. DataPartition.m is used to randomly partition the original data into training sets and test sets with a ratio of 7

Learning where to learn - Gradient sparsity in meta and continual learning In this paper, we investigate gradient sparsity found by MAML in various co

Gradient Inversion with Generative Image Prior This repository is an implementation of "Gradient Inversion with Generative Image Prior", accepted to N

Rapid is an open-source software library that implements a novel “parallel-in-time” (Parareal) algorithm and semi-analytical solutions for co-simulation of integrated transmission and distribution systems.

SGD-Linear-Regressor Iterative stochastic gradient descent (SGD) linear regressor with regularization Dataset: Kaggle “Graduate Admission 2” https://w

AA-RMVSNet Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021) in PyTorch. paper link: arXiv | CVF Change Log Ju

NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti

This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I

Adaptive wavelets Wavelets which adapt given data (and optionally a pre-trained model). This yields models which are faster, more compressible, and mo

Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods This repository is the official implementation of Seohong Park, Jaeky

Stochastic Gradient Trees - Python Stochastic Gradient Trees1 by Henry Gouk, Bernhard Pfahringer, and Eibe Frank implementation in Python. Based on th

Optimal Adaptive Allocation using Deep Reinforcement Learning in a Dose-Response Study Supplementary Materials for Kentaro Matsuura, Junya Honda, Imad

FS-QAT: Few Shot Temporal Action Localization using Query Adaptive Transformer Accepted as Poster in BMVC 2021 This is an official implementation in P

CxGrad - Official PyTorch Implementation Contextual Gradient Scaling for Few-Shot Learning Sanghyuk Lee, Seunghyun Lee, and Byung Cheol Song In WACV 2

MEND: Model Editing Networks using Gradient Decomposition Setup Environment This codebase uses Python 3.7.9. Other versions may work as well. Create a

BoMb-OT Python3 implementation of the papers On Transportation of Mini-batches: A Hierarchical Approach and Improving Mini-batch Optimal Transport via

AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation A pytorch-version implementation codes of paper:

pytorch-AdaIN This is an unofficial pytorch implementation of a paper, Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization [Hua

Ranger-Deep-Learning-Optimizer Ranger - a synergistic optimizer combining RAdam (Rectified Adam) and LookAhead, and now GC (gradient centralization) i

[NeurIPS 2021 Spotlight] HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning [Paper] This is Official PyTorch implementatio

Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient This repository is the official PyTorch implementation of "Edge Rewiring Go

PyTorch implementation of Constrained Policy Optimization (CPO) This repository has a simple to understand and use implementation of CPO in PyTorch. A

ttopt Description Gradient-free global optimization algorithm for multidimensional functions based on the low rank tensor train (TT) format and maximu

Variable-Rate Deep Image Compression through Spatially-Adaptive Feature Transform This repository is the implementation of "Variable-Rate Deep Image C

Codebase for learning control flow in transformers The official repository for our paper "The Neural Data Router: Adaptive Control Flow in Transformer

ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network This repository is the implementation of ACE-HGNN in PyTorch. Environment pyt

An adaptive hierarchical energy management strategy This project contains the source code of an adaptive hierarchical EMS combining heuristic equivale

AITM TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework. Code for the paper accepted by KDD21: Modeling the Sequen

pyHype: Computational Fluid Dynamics in Python pyHype is a Python framework for developing parallelized Computational Fluid Dynamics software to solve

This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I

revisiting-sepconv This is a reference implementation of Revisiting Adaptive Convolutions for Video Frame Interpolation [1] using PyTorch. Given two f

LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning, NeurIPS 2021 (Spotlight) Abstract Due to the limited and even imbalanced dat

LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation by Junjue Wang, Zhuo Zheng, Ailong Ma, Xiaoyan Lu, and Yanfei Zh

BasicRL: easy and fundamental codes for deep reinforcement learning BasicRL is an improvement on rainbow-is-all-you-need and OpenAI Spinning Up. It is

DAS Dual Adaptive Sampling for Machine Learning Interatomic potential. How to cite If you use this code in your research, please cite this using: Hong

AutoDSP TLDR; Train custom adaptive filter optimizers without hand tuning or extra labels. About Adaptive filtering algorithms are commonplace in sign

SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo

AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition [ArXiv] [Project Page] This repository is the official implementation of AdaMML:

Source code for the paper "Gradient Step Denoiser for convergent Plug-and-Play"

Stochastic Training is Not Necessary for Generalization -- Training competitive vision models without stochasticity This repository implements trainin

Code and result about CCAFNet(IEEE TMM) 'CCAFNet: Crossflow and Cross-scale Adaptive Fusion Network for Detecting Salient Objects in RGB-D Images' IEE

Ad^2Attack：Adaptive Adversarial Attack on Real-Time UAV Tracking Demo video 📹 Our video on bilibili demonstrates the test results of Ad^2Attack on se

Convolutional Neural Network Visualizations This repository contains a number of convolutional neural network visualization techniques implemented in

SpyTorch A tutorial on surrogate gradient learning in spiking neural networks Version: 0.4 This repository contains tutorial files to get you started

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

geoopt Manifold aware pytorch.optim. Unofficial implementation for “Riemannian Adaptive Optimization Methods” ICLR2019 and more. Installation Make sur

RAdam On the Variance of the Adaptive Learning Rate and Beyond We are in an early-release beta. Expect some adventures and rough edges. Table of Conte

Intro PyTorch implementation of Learning to learn by gradient descent by gradient descent. Run python main.py TODO Initial implementation Toy data LST

DEPRECATION This repository is deprecated and is no longer maintaned. Please see a more recent implementation of RL for continuous control at jax-sac.

Adaptive Graph Convolution for Point Cloud Analysis This repository contains the implementation of AdaptConv for point cloud analysis. Adaptive Graph

Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019) Introduction Official implementation of Adaptive Pyramid Context Network

IFAN: Iterative Filter Adaptive Network for Single Image Defocus Deblurring Checkout for the demo (GUI/Google Colab)! The GUI version might occasional

AdaFocus (ICCV 2021) This repo contains the official code and pre-trained models for AdaFocus. Adaptive Focus for Efficient Video Recognition Referenc

Ponder(ing) Transformer Implementation of a Transformer that learns to adapt the number of computational steps it takes depending on the difficulty of

Ponder(ing) Transformer Implementation of a Transformer that learns to adapt the number of computational steps it takes depending on the difficulty of

Heteroskedastic and Imbalanced Deep Learning with Adaptive Regularization Kaidi Cao, Yining Chen, Junwei Lu, Nikos Arechiga, Adrien Gaidon, Tengyu Ma

Pixel-Level Cycle Association This is the Pytorch implementation of our NeurIPS 2020 Oral paper Pixel-Level Cycle Association: A New Perspective for D

This repo is the official implementation of our paper "Instance Adaptive Self-training for Unsupervised Domain Adaptation". The purpose of this repo is to better communicate with you and respond to your questions. This repo is almost the same with Another-Version, and you can also refer to that version.

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks This is a Python3 / Pytorch implementation of TadGAN paper. The associated

Sequence Feature Alignment (SFA) By Wen Wang, Yang Cao, Jing Zhang, Fengxiang He, Zheng-jun Zha, Yonggang Wen, and Dacheng Tao This repository is an o

Gradient Episodic Memory for Continual Learning Source code for the paper: @inproceedings{GradientEpisodicMemory, title={Gradient Episodic Memory

Noisy Natural Gradient as Variational Inference PyTorch implementation of Noisy Natural Gradient as Variational Inference. Requirements Python 3 Pytor