915 Repositories
Python Attention-CLX-stock-prediction Libraries
pytorch implementation of Attention is all you need
A Pytorch Implementation of the Transformer: Attention Is All You Need Our implementation is largely based on Tensorflow implementation Requirements N
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V
Intent parsing and slot filling in PyTorch with seq2seq + attention
PyTorch Seq2Seq Intent Parsing Reframing intent parsing as a human - machine translation task. Work in progress successor to torch-seq2seq-intent-pars
Improving Convolutional Networks via Attention Transfer (ICLR 2017)
Attention Transfer PyTorch code for "Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Tran
Official implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
CrossViT This repository is the official implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification. ArXiv If
Learnable Multi-level Frequency Decomposition and Hierarchical Attention Mechanism for Generalized Face Presentation Attack Detection
LMFD-PAD Note This is the official repository of the paper: LMFD-PAD: Learnable Multi-level Frequency Decomposition and Hierarchical Attention Mechani
Learning based AI for playing multi-round Koi-Koi hanafuda card games. Have fun.
Koi-Koi AI Learning based AI for playing multi-round Koi-Koi hanafuda card games. Platform Python PyTorch PySimpleGUI (for the interface playing vs AI
[ICCV 2021] FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
FaPN: Feature-aligned Pyramid Network for Dense Image Prediction [arXiv] [Project Page] @inproceedings{ huang2021fapn, title={{FaPN}: Feature-alig
Code of paper "Compositionally Generalizable 3D Structure Prediction"
Compositionally Generalizable 3D Structure Prediction In this work, We bring in the concept of compositional generalizability and factorizes the 3D sh
Implementation of a Transformer, but completely in Triton
Transformer in Triton (wip) Implementation of a Transformer, but completely in Triton. I'm completely new to lower-level neural net code, so this repo
Technical Indicators implemented in Python only using Numpy-Pandas as Magic - Very Very Fast! Very tiny! Stock Market Financial Technical Analysis Python library . Quant Trading automation or cryptocoin exchange
MyTT Technical Indicators implemented in Python only using Numpy-Pandas as Magic - Very Very Fast! to Stock Market Financial Technical Analysis Python
Implementation of Hierarchical Transformer Memory (HTM) for Pytorch
Hierarchical Transformer Memory (HTM) - Pytorch Implementation of Hierarchical Transformer Memory (HTM) for Pytorch. This Deepmind paper proposes a si
Keras attention models including botnet,CoaT,CoAtNet,CMT,cotnet,halonet,resnest,resnext,resnetd,volo,mlp-mixer,resmlp,gmlp,levit
Keras_cv_attention_models Keras_cv_attention_models Usage Basic Usage Layers Model surgery AotNet ResNetD ResNeXt ResNetQ BotNet VOLO ResNeSt HaloNet
MVGCN: a novel multi-view graph convolutional network (MVGCN) framework for link prediction in biomedical bipartite networks.
MVGCN MVGCN: a novel multi-view graph convolutional network (MVGCN) framework for link prediction in biomedical bipartite networks. Developer: Fu Hait
[ICCV 2021] Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Counterfactual Attention Learning Created by Yongming Rao*, Guangyi Chen*, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for ICCV
A stock information collector and parser for Taiwan and US market. Automatically send LINE message if the pre-defined rules are triggered.
agastock 開發動機 就在海運飆漲的2021年7月,差點跪在地上喜迎財富自由的當下,EPS超高好消息不斷的長榮竟然套在202元一去不回,有圖有真相(哭) 忽然體會到追高殺低不是辦法,魯蛇我得靠邏輯分析也能出頭天,經過三個月無數個不出門的周末,產出簡單的爬蟲和分析工具。 上過金融研訓院的量化交易
【Arxiv】Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution
SANet Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution Dependencies numpy==1.18.5 scikit_image==0.16.2 torchvision==0.8.1 to
Normal Learning in Videos with Attention Prototype Network
Codes_APN Official codes of CVPR21 paper: Normal Learning in Videos with Attention Prototype Network (https://arxiv.org/abs/2108.11055) Overview of ou
A Deep Reinforcement Learning Framework for Stock Market Trading
DQN-Trading This is a framework based on deep reinforcement learning for stock market trading. This project is the implementation code for the two pap
Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting (ICCV, 2021)
DKPNet ICCV 2021 Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting Baseline of DKPNet is availa
[ICCV 2021] Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification
Counterfactual Attention Learning Created by Yongming Rao*, Guangyi Chen*, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for ICCV
Efficient Conformer: Progressive Downsampling and Grouped Attention for Automatic Speech Recognition
Efficient Conformer: Progressive Downsampling and Grouped Attention for Automatic Speech Recognition Official implementation of the Efficient Conforme
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
Stock Market Insights is a Dashboard that gives the 360 degree view of the particular company stock
Stock Market Insights is a Dashboard that gives the 360 degree view of the particular company stock.It extracts specific data from multiple sources like Social Media (Twitter,Reddit ,StockTwits) , News Articles and applies NLP techniques to get sentiments and insights.
Implementation for our ICCV 2021 paper: Dual-Camera Super-Resolution with Aligned Attention Modules
DCSR: Dual Camera Super-Resolution Implementation for our ICCV 2021 oral paper: Dual-Camera Super-Resolution with Aligned Attention Modules paper | pr
[ICCV 2021] Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation
MAED: Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation Getting Started Our codes are implemented and tested with pyth
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019)
Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019) Introduction Official implementation of Adaptive Pyramid Context Network
multi-label,classifier,text classification,多标签文本分类,文本分类,BERT,ALBERT,multi-label-classification,seq2seq,attention,beam search
multi-label,classifier,text classification,多标签文本分类,文本分类,BERT,ALBERT,multi-label-classification,seq2seq,attention,beam search
Unofficial Tensorflow-Keras implementation of Fastformer based on paper [Fastformer: Additive Attention Can Be All You Need](https://arxiv.org/abs/2108.09084).
Fastformer-Keras Unofficial Tensorflow-Keras implementation of Fastformer based on paper Fastformer: Additive Attention Can Be All You Need. Tensorflo
Implementation for our ICCV 2021 paper: Dual-Camera Super-Resolution with Aligned Attention Modules
DCSR: Dual Camera Super-Resolution Implementation for our ICCV 2021 oral paper: Dual-Camera Super-Resolution with Aligned Attention Modules paper | pr
🥈78th place in Riiid Answer Correctness Prediction competition
Riiid Answer Correctness Prediction Introduction This repository is the code that placed 78th in Riiid Answer Correctness Prediction competition. Requ
Streamlit Tutorial (ex: stock price dashboard, cartoon-stylegan, vqgan-clip, stylemixing, styleclip, sefa)
Streamlit Tutorials Install pip install streamlit Run cd [directory] streamlit run app.py --server.address 0.0.0.0 --server.port [your port] # http:/
An implementation of Fastformer: Additive Attention Can Be All You Need in TensorFlow
Fast Transformer This repo implements Fastformer: Additive Attention Can Be All You Need by Wu et al. in TensorFlow. Fast Transformer is a Transformer
[ICCV 2021] Released code for Causal Attention for Unbiased Visual Recognition
CaaM This repo contains the codes of training our CaaM on NICO/ImageNet9 dataset. Due to my recent limited bandwidth, this codebase is still messy, wh
A novel benchmark dataset for Monocular Layout prediction
AutoLay AutoLay: Benchmarking Monocular Layout Estimation Kaustubh Mani, N. Sai Shankar, J. Krishna Murthy, and K. Madhava Krishna Abstract In this pa
Official code of ICCV2021 paper "Residual Attention: A Simple but Effective Method for Multi-Label Recognition"
CSRA This is the official code of ICCV 2021 paper: Residual Attention: A Simple But Effective Method for Multi-Label Recoginition Demo, Train and Vali
🌈 PyTorch Implementation for EMNLP'21 Findings "Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer"
SGLKT-VisDial Pytorch Implementation for the paper: Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer Gi-Cheon Kang, Junseok P
Unofficial PyTorch implementation of Fastformer based on paper "Fastformer: Additive Attention Can Be All You Need"."
Fastformer-PyTorch Unofficial PyTorch implementation of Fastformer based on paper Fastformer: Additive Attention Can Be All You Need. Usage : import t
Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs
Perceiver IO Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs Usage import torch from src.perceiver.
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
Discriminative Region-based Multi-Label Zero-Shot Learning (ICCV 2021) [arXiv][Project page coming soon] Sanath Narayan*, Akshita Gupta*, Salman Kh
Implementation of Fast Transformer in Pytorch
Fast Transformer - Pytorch Implementation of Fast Transformer in Pytorch. This only work as an encoder. Yannic video AI Epiphany Install $ pip install
[ICCV 2021] Official Pytorch implementation for Discriminative Region-based Multi-Label Zero-Shot Learning SOTA results on NUS-WIDE and OpenImages
Discriminative Region-based Multi-Label Zero-Shot Learning (ICCV 2021) [arXiv][Project page coming soon] Sanath Narayan*, Akshita Gupta*, Salman Kh
Intent parsing and slot filling in PyTorch with seq2seq + attention
PyTorch Seq2Seq Intent Parsing Reframing intent parsing as a human - machine translation task. Work in progress successor to torch-seq2seq-intent-pars
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V
Implementation of Fast Transformer in Pytorch
Fast Transformer - Pytorch Implementation of Fast Transformer in Pytorch. This only work as an encoder. Yannic video AI Epiphany Install $ pip install
Official Python wrapper for the Quantel Finance API
Quantel is a powerful financial data and insights API. It provides easy access to world-class financial information. Quantel goes beyond just financial statements, giving users valuable information like insider transactions, major shareholder transactions, share ownership, peers, and so much more.
This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes.
Rotate-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes. Section I. Description The codes are
Official code for "Focal Self-attention for Local-Global Interactions in Vision Transformers"
Focal Transformer This is the official implementation of our Focal Transformer -- "Focal Self-attention for Local-Global Interactions in Vision Transf
[ICCV'21] NEAT: Neural Attention Fields for End-to-End Autonomous Driving
NEAT: Neural Attention Fields for End-to-End Autonomous Driving Paper | Supplementary | Video | Poster | Blog This repository is for the ICCV 2021 pap
Context Axial Reverse Attention Network for Small Medical Objects Segmentation
CaraNet: Context Axial Reverse Attention Network for Small Medical Objects Segmentation This repository contains the implementation of a novel attenti
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).
Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv
This is an official implementation of the High-Resolution Transformer for Dense Prediction.
High-Resolution Transformer for Dense Prediction Introduction This is the official implementation of High-Resolution Transformer (HRT). We present a H
Churn prediction with PySpark
It is expected to develop a machine learning model that can predict customers who will leave the company.
LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION
Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp
The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).
The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).
Stacked Hourglass Network with a Multi-level Attention Mechanism: Where to Look for Intervertebral Disc Labeling
⚠️ A more recent and actively-maintained version of this code is available in ivadomed Stacked Hourglass Network with a Multi-level Attention Mech
Official code for "Stereo Waterdrop Removal with Row-wise Dilated Attention (IROS2021)"
Stereo-Waterdrop-Removal-with-Row-wise-Dilated-Attention This repository includes official codes for "Stereo Waterdrop Removal with Row-wise Dilated A
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.
An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l
Homepage of paper: Paint Transformer: Feed Forward Neural Painting with Stroke Prediction, ICCV 2021.
Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [PaddlePaddle Implementation] Homepage of paper: Paint Transformer: Fee
Using VideoBERT to tackle video prediction
VideoBERT This repo reproduces the results of VideoBERT (https://arxiv.org/pdf/1904.01766.pdf). Inspiration was taken from https://github.com/MDSKUL/M
Simple plug-and-play installer for users who want to LineageOS from stock firmware, or from another custom ROM.
LineageOS for the Teracube 2e Simple plug-and-play installer for users who want to LineageOS from stock firmware, or from another custom ROM. Dependen
How to Become More Salient? Surfacing Representation Biases of the Saliency Prediction Model
How to Become More Salient? Surfacing Representation Biases of the Saliency Prediction Model
PyTorch implementation of paper: AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer, ICCV 2021.
AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer [Paper] [PyTorch Implementation] [Paddle Implementation] Overview This reposit
Investigating Attention Mechanism in 3D Point Cloud Object Detection (arXiv 2021)
Investigating Attention Mechanism in 3D Point Cloud Object Detection (arXiv 2021) This repository is for the following paper: "Investigating Attention
Scenic: A Jax Library for Computer Vision and Beyond
Scenic Scenic is a codebase with a focus on research around attention-based models for computer vision. Scenic has been successfully used to develop c
[CVPR 2021] Forecasting the panoptic segmentation of future video frames
Panoptic Segmentation Forecasting Colin Graber, Grace Tsai, Michael Firman, Gabriel Brostow, Alexander Schwing - CVPR 2021 [Link to paper] We propose
Code for paper "ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation"
ASAP-Net This project implements ASAP-Net of paper ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation (BMVC2020). Overview We i
Dense Prediction Transformers
Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,
This is the codebase for the ICLR 2021 paper Trajectory Prediction using Equivariant Continuous Convolution
Trajectory Prediction using Equivariant Continuous Convolution (ECCO) This is the codebase for the ICLR 2021 paper Trajectory Prediction using Equivar
"Inductive Entity Representations from Text via Link Prediction" @ The Web Conference 2021
Inductive entity representations from text via link prediction This repository contains the code used for the experiments in the paper "Inductive enti
A modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (prediction model)
ParallelFold Author: Bozitao Zhong This is a modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (p
The code for our paper CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention.
CrossFormer This repository is the code for our paper CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention. Introduction Existin
An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge.
Bottom-Up and Top-Down Attention for Visual Question Answering An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge. The
pytorch implementation of Attention is all you need
A Pytorch Implementation of the Transformer: Attention Is All You Need Our implementation is largely based on Tensorflow implementation Requirements N
Train an RL agent to execute natural language instructions in a 3D Environment (PyTorch)
Gated-Attention Architectures for Task-Oriented Language Grounding This is a PyTorch implementation of the AAAI-18 paper: Gated-Attention Architecture
Wind Speed Prediction using LSTMs in PyTorch
Implementation of Deep-Forecast using PyTorch Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting Adapted from original implementation Setu
This's an implementation of deepmind Visual Interaction Networks paper using pytorch
Visual-Interaction-Networks An implementation of Deepmind visual interaction networks in Pytorch. Introduction For the purpose of understanding the ch
LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.
LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.
A Structured Self-attentive Sentence Embedding
Structured Self-attentive sentence embeddings Implementation for the paper A Structured Self-Attentive Sentence Embedding, which was published in ICLR
Bilinear attention networks for visual question answering
Bilinear Attention Networks This repository is the implementation of Bilinear Attention Networks for the visual question answering and Flickr30k Entit
A PyTorch Implementation of the Luna: Linear Unified Nested Attention
Unofficial PyTorch implementation of Luna: Linear Unified Nested Attention The quadratic computational and memory complexities of the Transformer’s at
Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning
H-Transformer-1D Implementation of H-Transformer-1D, Transformer using hierarchical Attention for sequence learning with subquadratic costs. For now,
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
This is an official implementation of "Polarized Self-Attention: Towards High-quality Pixel-wise Regression"
Polarized Self-Attention: Towards High-quality Pixel-wise Regression This is an official implementation of: Huajun Liu, Fuqiang Liu, Xinyi Fan and Don
PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
VAENAR-TTS - PyTorch Implementation PyTorch Implementation of VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis.
Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Context Terms
LESA Introduction This repository contains the official implementation of Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Cont
Implementation of "A MLP-like Architecture for Dense Prediction"
A MLP-like Architecture for Dense Prediction (arXiv) Updates (22/07/2021) Initial release. Model Zoo We provide CycleMLP models pretrained on ImageNet
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
An implementation of DeepMind's Relational Recurrent Neural Networks in PyTorch.
relational-rnn-pytorch An implementation of DeepMind's Relational Recurrent Neural Networks (Santoro et al. 2018) in PyTorch. Relational Memory Core (
Pytorch implementation of face attention network
Face Attention Network Pytorch implementation of face attention network as described in Face Attention Network: An Effective Face Detector for the Occ
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
Attention Walk ⠀⠀ A PyTorch Implementation of Watch Your Step: Learning Node Embeddings via Graph Attention (NIPS 2018). Abstract Graph embedding meth
A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).
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
A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).
GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
SimGNN ⠀⠀⠀ A PyTorch implementation of SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019). Abstract Graph similarity s
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).
APPNP ⠀ A PyTorch implementation of Predict then Propagate: Graph Neural Networks meet Personalized PageRank (ICLR 2019). Abstract Neural message pass
An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).
MixHop and N-GCN ⠀ A PyTorch implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019)
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
CapsGNN ⠀⠀ A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019). Abstract The high-quality node embeddings learned from the Graph Neur