Python Vrp-attention-jax Resources

Face Attention Network Pytorch implementation of face attention network as described in Face Attention Network: An Effective Face Detector for the Occ

English | 简体中文 | 繁體中文 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained mo

Attention Walk ⠀⠀ A PyTorch Implementation of Watch Your Step: Learning Node Embeddings via Graph Attention (NIPS 2018). Abstract Graph embedding meth

SGCN ⠀ A PyTorch implementation of Signed Graph Convolutional Network (ICDM 2018). Abstract Due to the fact much of today's data can be represented as

GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic

SimGNN ⠀⠀⠀ A PyTorch implementation of SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019). Abstract Graph similarity s

APPNP ⠀ A PyTorch implementation of Predict then Propagate: Graph Neural Networks meet Personalized PageRank (ICLR 2019). Abstract Neural message pass

MixHop and N-GCN ⠀ A PyTorch implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019)

CapsGNN ⠀⠀ A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019). Abstract The high-quality node embeddings learned from the Graph Neur

Clockwork VAEs in JAX/Flax Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax, ported

RoBERTa base model for Marathi Language (मराठी भाषा) Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa wa

VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.

PIX PIX is an image processing library in JAX, for JAX. Overview JAX is a library resulting from the union of Autograd and XLA for high-performance ma

Invariant Point Attention - Pytorch Implementation of Invariant Point Attention as a standalone module, which was used in the structure module of Alph

DSA^2 F: Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion (CVPR'2021, Oral) This repo is the official imp

HAN PyTorch code for our ECCV 2020 paper "Single Image Super-Resolution via a Holistic Attention Network" This repository is for HAN introduced in the

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. 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).

Plug-and-play Module Plug and play transformer you can find network structure and official complete code by clicking List The following is to quickly

A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.

Image Super-Resolution with Non-Local Sparse Attention This repository is for NLSN introduced in the following paper "Image Super-Resolution with Non-

A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.

UACANet: Uncertainty Aware Context Attention for Polyp Segmentation Official pytorch implementation of UACANet: Uncertainty Aware Context Attention fo

2021-MICCAI-Progressively Normalized Self-Attention Network for Video Polyp Segmentation Authors: Ge-Peng Ji*, Yu-Cheng Chou*, Deng-Ping Fan, Geng Che

TS-CAM: Token Semantic Coupled Attention Map for Weakly SupervisedObject Localization This is the official implementaion of paper TS-CAM: Token Semant

SWAL Code for Paper "Selective Wavelet Attention Learning for Single Image Deraining" Prerequisites Python 3 PyTorch Models We provide the models trai

Dual Self-Attention Network for Multivariate Time Series Forecasting 20.10.26 Update: Due to the difficulty of installation and code maintenance cause

flax-sentence-embeddings This repository will be used to share code for the Flax / JAX community event to train sentence embeddings on 1B+ training pa

ProGen - (wip) Implementation and replication of ProGen, Language Modeling for Protein Generation, in Pytorch and Jax (the weights will be made easily

MTTS-CAN: Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement Paper Xin Liu, Josh Fromm, Shwetak Patel, Daniel M

A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.

[TensorFlow] Attention mechanism with MNIST dataset Usage $ python run.py Result Training Loss graph. Test Each figure shows input digit, attention ma

Shared Attention for Multi-label Zero-shot Learning Overview This repository contains the implementation of Shared Attention for Multi-label Zero-shot

FitVid Video Prediction Model Implementation of FitVid video prediction model in JAX/Flax. If you find this code useful, please cite it in your paper:

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).

DLCF-DCA codes for paper Combining Dynamic Local Context Focus and Dependency Cluster Attention for Aspect-level sentiment classification. submitted t

FinGAT: A Financial Graph Attention Networkto Recommend Top-K Profitable Stocks This is our implementation for the paper: FinGAT: A Financial Graph At

Python code for "Machine learning: a probabilistic perspective" (2nd edition)

Episodic Transformers (E.T.) Episodic Transformer for Vision-and-Language Navigation Alexander Pashevich, Cordelia Schmid, Chen Sun Episodic Transform

LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant Self-At

Toy implementations of some popular ML optimizers using Python/JAX

NesT is a simple method, which aggragrates nested local transformers on image blocks. The idea makes vision transformers attain better accuracy, data efficiency, and convergence on the ImageNet benchmark. NesT can be scaled to small datasets to match convnet accuracy.

Uformer - Pytorch Implementation of Uformer, Attention-based Unet, in Pytorch. It will only offer the concat-cross-skip connection. This repository wi

SA-MobileNetV3 Shuffle Attention for MobileNetV3 Train Run the following command for train model on your own dataset: python train.py --dataset mnist

EPSANet：An Efficient Pyramid Split Attention Block on Convolutional Neural Network This repo contains the official Pytorch implementaion code and conf

Motionformer This is an official pytorch implementation of paper Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. In this rep

FANet Real-time Semantic Segmentation with Fast Attention Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko , Stan Sc

CAT: Cross Attention in Vision Transformer This is official implement of "CAT: Cross Attention in Vision Transformer". Abstract Since Transformer has

Optimal Model Design for Reinforcement Learning This repository contains JAX code for the paper Control-Oriented Model-Based Reinforcement Learning wi

Segformer - Pytorch Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch. Install $ pip install segformer-pytorch

Less is More: Pay Less Attention in Vision Transformers Official PyTorch implementation of Less is More: Pay Less Attention in Vision Transformers. By

This repository is the official PyTorch implementation of SAINT. Find the paper on arxiv SAINT: Improved Neural Networks for Tabular Data via Row Atte

jax_dataclasses jax_dataclasses provides a wrapper around dataclasses.dataclass for use in JAX, which enables automatic support for: Pytree registrati

We challenge a common assumption underlying most supervised deep learning: that a model makes a prediction depending only on its parameters and the features of a single input. To this end, we introduce a general-purpose deep learning architecture that takes as input the entire dataset instead of processing one datapoint at a time.

aft-pytorch Unofficial PyTorch implementation of Attention Free Transformer's layers by Zhai, et al. [abs, pdf] from Apple Inc. Installation You can i

gMLP PyTorch implementation of Pay Attention to MLPs. Quickstart Clone this repository. git clone https://github.com/jaketae/g-mlp.git Navigate to th

SYMPAIS: Symbolic Parallel Adaptive Importance Sampling for Probabilistic Program Analysis Overview | Installation | Documentation | Examples | Notebo

Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks paper : https://arxiv.org/abs/2105.02358 EAMLP will come soon Jitto

How Attentive are Graph Attention Networks? This repository is the official implementation of How Attentive are Graph Attention Networks?. The PyTorch

Attention-driven Robotic Manipulation (ARM) This codebase is home to: Q-attention: Enabling Efficient Learning for Vision-based Robotic Manipulation I

MLP-Mixer-CIFAR10 This repository implements MLP-Mixer as proposed in MLP-Mixer: An all-MLP Architecture for Vision. The paper introduces an all MLP (

CrossViT : Cross-Attention Multi-Scale Vision Transformer for Image Classification This is an unofficial PyTorch implementation of CrossViT: Cross-Att

Neural Attention Distillation This is an implementation demo of the ICLR 2021 paper Neural Attention Distillation: Erasing Backdoor Triggers from Deep

Factor graphs + nonlinear optimization in JAX

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Attention-guided Temporal Coherent Video Object Matting This is the Github project for our paper Attention-guided Temporal Coherent Video Object Matti

Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching Official pytorch implementation of "Show, Attend and Distill: Kn

Local Attention - Flax Autoregressive Local Attention - Flax module for Jax Install $ pip install local-attention-flax Usage from jax import random fr

BRIMs Bidirectional Recurrent Independent Mechanisms Implementation of the paper Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neura

MLP GPT - Jax (wip) A GPT, made only of MLPs, in Jax. The specific MLP to be used are gMLPs with the Spatial Gating Units. Working Pytorch implementat

Under construction... Attention in Attention Network for Image Super-Resolution (A2N) This repository is an PyTorch implementation of the paper "Atten

Mixed precision training [0] is a technique that mixes the use of full and half precision floating point numbers during training to reduce the memory bandwidth requirements and improve the computational efficiency of a given model.

Parallel Tacotron2 Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

Vision Transformers are Robust Learners This repository contains the code for the paper Vision Transformers are Robust Learners by Sayak Paul* and Pin

Sabertooth Sabertooth is standalone pre-training recipe based on JAX+Flax, with data pipelines implemented in Rust. It runs on CPU, GPU, and/or TPU, b

DroneCrowd Paper Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark. Introduction This paper proposes a space-time multi-scale atte

Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks paper : https://arxiv.org/abs/2105.02358 Jittor code will come soon

Pretrained models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet.

Bayesian optimization in JAX

Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet Paper/Report TL;DR We replace the attention layer in a v

Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH

Twins: Revisiting the Design of Spatial Attention in Vision Transformers Very recently, a variety of vision transformer architectures for dense predic

coax is built on top of JAX, but it doesn't have an explicit dependence on the jax python package. The reason is that your version of jaxlib will depend on your CUDA version.

Human Attention for Text Classification Re-implementation of the paper Human Attention Maps for Text Classification: Do Humans and Neural Networks Foc

Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet

CeiT : Convolutional enhanced image Transformer This is an unofficial PyTorch implementation of Incorporating Convolution Designs into Visual Transfor

Perceiver This Python package implements Perceiver: General Perception with Iterative Attention by Andrew Jaegle in TensorFlow. This model builds on t

TimeSformer This is an official pytorch implementation of Is Space-Time Attention All You Need for Video Understanding?. In this repository, we provid

MASTER-PyTorch PyTorch reimplementation of "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021). This projec

Cross Transformers - Pytorch (wip) Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch Install $ pip install cross-t

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Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)

TransGanFormer (wip) Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. I

PyTorch Implementation of Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers 1 Using Colab Please notic

SiamGAT 1. Environment setup This code has been tested on Ubuntu 16.04, Python 3.5, Pytorch 1.2.0, CUDA 9.0. Please install related libraries before r

Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. This paper presents a new vision Transformer, called Swin Transformer,

STAM - Pytorch Implementation of STAM (Space Time Attention Model), yet another pure and simple SOTA attention model that bests all previous models in

Funsor Funsor is a tensor-like library for functions and distributions. See Functional tensors for probabilistic programming for a system description.

Lambda Networks - Pytorch Implementation of λ Networks, a new approach to image recognition that reaches SOTA on ImageNet. The new method utilizes λ l

Performer - Pytorch An implementation of Performer, a linear attention-based transformer variant with a Fast Attention Via positive Orthogonal Random