5403 Repositories
Python quantum-machine-learning Libraries
Code in conjunction with the publication 'Contrastive Representation Learning for Hand Shape Estimation'
HanCo Dataset & Contrastive Representation Learning for Hand Shape Estimation Code in conjunction with the publication: Contrastive Representation Lea
[CVPR2021] Look before you leap: learning landmark features for one-stage visual grounding.
LBYL-Net This repo implements paper Look Before You Leap: Learning Landmark Features For One-Stage Visual Grounding CVPR 2021. Getting Started Prerequ
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences [CVPR2021]
Patch2Pix for Accurate Image Correspondence Estimation This repository contains the Pytorch implementation of our paper accepted at CVPR2021: Patch2Pi
ShapeGlot: Learning Language for Shape Differentiation
ShapeGlot: Learning Language for Shape Differentiation Created by Panos Achlioptas, Judy Fan, Robert X.D. Hawkins, Noah D. Goodman, Leonidas J. Guibas
Machine Unlearning with SISA
Machine Unlearning with SISA Lucas Bourtoule, Varun Chandrasekaran, Christopher Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, N
Weighing Counts: Sequential Crowd Counting by Reinforcement Learning
LibraNet This repository includes the official implementation of LibraNet for crowd counting, presented in our paper: Weighing Counts: Sequential Crow
This is the pytorch code for the paper Curious Representation Learning for Embodied Intelligence.
Curious Representation Learning for Embodied Intelligence This is the pytorch code for the paper Curious Representation Learning for Embodied Intellig
Official repository for the paper "Going Beyond Linear Transformers with Recurrent Fast Weight Programmers"
Recurrent Fast Weight Programmers This is the official repository containing the code we used to produce the experimental results reported in the pape
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing
PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing
pure-predict: Machine learning prediction in pure Python
pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks like scikit-learn and fasttext. It implements the predict methods of these frameworks in pure Python.
ACL'2021: Learning Dense Representations of Phrases at Scale
DensePhrases DensePhrases is an extractive phrase search tool based on your natural language inputs. From 5 million Wikipedia articles, it can search
Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2
Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot
Official PyTorch Implementation of Embedding Transfer with Label Relaxation for Improved Metric Learning, CVPR 2021
Embedding Transfer with Label Relaxation for Improved Metric Learning Official PyTorch implementation of CVPR 2021 paper Embedding Transfer with Label
Implementation of the GBST block from the Charformer paper, in Pytorch
Charformer - Pytorch Implementation of the GBST (gradient-based subword tokenization) module from the Charformer paper, in Pytorch. The paper proposes
Falken provides developers with a service that allows them to train AI that can play their games
Falken provides developers with a service that allows them to train AI that can play their games. Unlike traditional RL frameworks that learn through rewards or batches of offline training, Falken is based on training AI via realtime, human interactions.
A python library to build Model Trees with Linear Models at the leaves.
A python library to build Model Trees with Linear Models at the leaves.
Deep Learning Models for Causal Inference
Extensive tutorials for learning how to build deep learning models for causal inference using selection on observables in Tensorflow 2.
A data preprocessing package for time series data. Design for machine learning and deep learning.
A data preprocessing package for time series data. Design for machine learning and deep learning.
This is a template for the Non-autoregressive Deep Learning-Based TTS model (in PyTorch).
Non-autoregressive Deep Learning-Based TTS Template This is a template for the Non-autoregressive TTS model. It contains Data Preprocessing Pipeline D
Meerkat provides fast and flexible data structures for working with complex machine learning datasets.
Meerkat makes it easier for ML practitioners to interact with high-dimensional, multi-modal data. It provides simple abstractions for data inspection, model evaluation and model training supported by efficient and robust IO under the hood.
Learning To Have An Ear For Face Super-Resolution
Learning To Have An Ear For Face Super-Resolution [Project Page] This repository contains demo code of our CVPR2020 paper. Training and evaluation on
Shared Attention for Multi-label Zero-shot Learning
Shared Attention for Multi-label Zero-shot Learning Overview This repository contains the implementation of Shared Attention for Multi-label Zero-shot
CLIP: Connecting Text and Image (Learning Transferable Visual Models From Natural Language Supervision)
CLIP (Contrastive Language–Image Pre-training) Experiments (Evaluation) Model Dataset Acc (%) ViT-B/32 (Paper) CIFAR100 65.1 ViT-B/32 (Our) CIFAR100 6
This repo is a PyTorch implementation for Paper "Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds"
Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds This repository is a PyTorch implementation for paper: Uns
Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data
SEDE SEDE (Stack Exchange Data Explorer) is new dataset for Text-to-SQL tasks with more than 12,000 SQL queries and their natural language description
Official Implement of CVPR 2021 paper “Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting”
RGBT Crowd Counting Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin. "Cross-Modal Collaborative Representation Learning and a L
Cross-Modal Contrastive Learning for Text-to-Image Generation
Cross-Modal Contrastive Learning for Text-to-Image Generation This repository hosts the open source JAX implementation of XMC-GAN. Setup instructions
AllenNLP integration for Shiba: Japanese CANINE model
Allennlp Integration for Shiba allennlp-shiab-model is a Python library that provides AllenNLP integration for shiba-model. SHIBA is an approximate re
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).
Gamestonk Terminal is an awesome stock and crypto market terminal
Gamestonk Terminal is an awesome stock and crypto market terminal. A FOSS alternative to Bloomberg Terminal.
LibTraffic is a unified, flexible and comprehensive traffic prediction library based on PyTorch
LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is implemented based on PyTorch, and includes all the necessary steps or components related to traffic prediction into a systematic pipeline.
30 Days Of Machine Learning Using Pytorch
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
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
Joint Learning of 3D Shape Retrieval and Deformation, CVPR 2021
Joint Learning of 3D Shape Retrieval and Deformation Joint Learning of 3D Shape Retrieval and Deformation Mikaela Angelina Uy, Vladimir G. Kim, Minhyu
Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch
Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS)
This repository is an implementation of Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS) with a vocoder that works in real-time. Feel free to check my thesis if you're curious or if you're looking for info I haven't documented. Mostly I would recommend giving a quick look to the figures beyond the introduction.
Lyapunov-guided Deep Reinforcement Learning for Stable Online Computation Offloading in Mobile-Edge Computing Networks
PyTorch code to reproduce LyDROO algorithm [1], which is an online computation offloading algorithm to maximize the network data processing capability subject to the long-term data queue stability and average power constraints. It applies Lyapunov optimization to decouple the multi-stage stochastic MINLP into deterministic per-frame MINLP subproblems and solves each subproblem via DROO algorithm. It includes:
Craxk is a SINGLE AND NON-REPLICABLE Hash that uses data from the hardware where it is executed to form a hash that can only be reproduced by a single machine.
What is Craxk ? Craxk is a UNIQUE AND NON-REPLICABLE Hash that uses data from the hardware where it is executed to form a hash that can only be reprod
Official Pytorch Implementation of: "Semantic Diversity Learning for Zero-Shot Multi-label Classification"(2021) paper
Semantic Diversity Learning for Zero-Shot Multi-label Classification Paper Official PyTorch Implementation Avi Ben-Cohen, Nadav Zamir, Emanuel Ben Bar
Orthogonal Over-Parameterized Training
The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great importance. We propose a novel orthogonal over-parameterized training (OPT) framework that can provably minimize the hyperspherical energy which characterizes the diversity of neurons on a hypersphere. See our previous work -- MHE for an in-depth introduction.
DeepProbLog is an extension of ProbLog that integrates Probabilistic Logic Programming with deep learning by introducing the neural predicate.
DeepProbLog DeepProbLog is an extension of ProbLog that integrates Probabilistic Logic Programming with deep learning by introducing the neural predic
Implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021).
[PDF] | [Slides] The official implementation of Learning Gradient Fields for Molecular Conformation Generation (ICML 2021 Long talk) Installation Inst
BridgeWalk is a partially-observed reinforcement learning environment with dynamics of varying stochasticity.
BridgeWalk is a partially-observed reinforcement learning environment with dynamics of varying stochasticity. The player needs to walk along a bridge to reach a goal location. When the player walks off the bridge into the water, the current will move it randomly until it gets washed back on the shore. A good agent in this environment avoids this stochastic trap
This repo will contain code to reproduce and build upon understanding transfer learning
What is being transferred in transfer learning? This repo contains the code for the following paper: Behnam Neyshabur*, Hanie Sedghi*, Chiyuan Zhang*.
BRepNet: A topological message passing system for solid models
BRepNet: A topological message passing system for solid models This repository contains the an implementation of BRepNet: A topological message passin
Meta-learning for NLP
Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks Code for training the meta-learning models and fine-tuning on downstr
MolRep: A Deep Representation Learning Library for Molecular Property Prediction
MolRep: A Deep Representation Learning Library for Molecular Property Prediction Summary MolRep is a Python package for fairly measuring algorithmic p
SmartSim Infrastructure Library.
Home Install Documentation Slack Invite Cray Labs SmartSim SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and Ten
[ICML 2021] Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data
Break-It-Fix-It: Learning to Repair Programs from Unlabeled Data This repo provides the source code & data of our paper: Break-It-Fix-It: Unsupervised
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering Jang Hyun Cho1, Utkarsh Mall2, Kavita Bala2, Bharath Harihar
CausaLM: Causal Model Explanation Through Counterfactual Language Models
CausaLM: Causal Model Explanation Through Counterfactual Language Models Authors: Amir Feder, Nadav Oved, Uri Shalit, Roi Reichart Abstract: Understan
PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Representation
How to Reproduce our Results This repository contains PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Represen
Outlier Exposure with Confidence Control for Out-of-Distribution Detection
OOD-detection-using-OECC This repository contains the essential code for the paper Outlier Exposure with Confidence Control for Out-of-Distribution De
Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image
NonCuboidRoom Paper Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image Cheng Yang*, Jia Zheng*, Xili Dai, Rui Tang, Yi Ma, Xiao
Code for "CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds" @ICRA2021
CloudAAE This is an tensorflow implementation of "CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds" Files log:
Official project website for the CVPR 2021 paper "Exploring intermediate representation for monocular vehicle pose estimation"
EgoNet Official project website for the CVPR 2021 paper "Exploring intermediate representation for monocular vehicle pose estimation". This repo inclu
Model-based 3D Hand Reconstruction via Self-Supervised Learning, CVPR2021
S2HAND: Model-based 3D Hand Reconstruction via Self-Supervised Learning S2HAND presents a self-supervised 3D hand reconstruction network that can join
Learning Neural Network Subspaces
Learning Neural Network Subspaces Welcome to the codebase for Learning Neural Network Subspaces by Mitchell Wortsman, Maxwell Horton, Carlos Guestrin,
Code for the RA-L (ICRA) 2021 paper "SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition"
SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition [ArXiv+Supplementary] [IEEE Xplore RA-L 2021] [ICRA 2021 YouTube Video]
The official implementation of the CVPR2021 paper: Decoupled Dynamic Filter Networks
Decoupled Dynamic Filter Networks This repo is the official implementation of CVPR2021 paper: "Decoupled Dynamic Filter Networks". Introduction DDF is
Code and data for "TURL: Table Understanding through Representation Learning"
TURL This Repo contains code and data for "TURL: Table Understanding through Representation Learning". Environment and Setup Data Pretraining Finetuni
Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020)
GraspNet Baseline Baseline model for "GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping" (CVPR 2020). [paper] [dataset] [API] [do
The AugNet Python module contains functions for the fast computation of image similarity.
AugNet AugNet: End-to-End Unsupervised Visual Representation Learning with Image Augmentation arxiv link In our work, we propose AugNet, a new deep le
Pretraining Representations For Data-Efficient Reinforcement Learning
Pretraining Representations For Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Ch
Megaverse is a new 3D simulation platform for reinforcement learning and embodied AI research
Megaverse Megaverse is a new 3D simulation platform for reinforcement learning and embodied AI research. The efficient design of the engine enables ph
Code for "Primitive Representation Learning for Scene Text Recognition" (CVPR 2021)
Primitive Representation Learning Network (PREN) This repository contains the code for our paper accepted by CVPR 2021 Primitive Representation Learni
Code for "LASR: Learning Articulated Shape Reconstruction from a Monocular Video". CVPR 2021.
LASR Installation Build with conda conda env create -f lasr.yml conda activate lasr # install softras cd third_party/softras; python setup.py install;
Official implementation of the paper DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows
DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows Official implementation of the paper DeFlow: Learning Complex Im
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow
SmartSim makes it easier to use common Machine Learning (ML) libraries like PyTorch and TensorFlow, in High Performance Computing (HPC) simulations and workloads.
JittorVis - Visual understanding of deep learning model.
JittorVis is a deep neural network computational graph visualization library based on Jittor.
The `rtdl` library + The official implementation of the paper
The `rtdl` library + The official implementation of the paper "Revisiting Deep Learning Models for Tabular Data"
Neighborhood Contrastive Learning for Novel Class Discovery
Neighborhood Contrastive Learning for Novel Class Discovery This repository contains the official implementation of our paper: Neighborhood Contrastiv
Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenes
An intelligent, flexible grammar of machine learning.
An english representation of machine learning. Modify what you want, let us handle the rest. Overview Nylon is a python library that lets you customiz
Pytorch implementation of Supporting Clustering with Contrastive Learning, NAACL 2021
Supporting Clustering with Contrastive Learning SCCL (NAACL 2021) Dejiao Zhang, Feng Nan, Xiaokai Wei, Shangwen Li, Henghui Zhu, Kathleen McKeown, Ram
Thermal Control of Laser Powder Bed Fusion using Deep Reinforcement Learning
This repository is the implementation of the paper "Thermal Control of Laser Powder Bed Fusion Using Deep Reinforcement Learning", linked here. The project makes use of the Deep Reinforcement Library stable-baselines3 to derive a control policy that maximizes melt pool depth consistency.
Patch Rotation: A Self-Supervised Auxiliary Task for Robustness and Accuracy of Supervised Models
Patch-Rotation(PatchRot) Patch Rotation: A Self-Supervised Auxiliary Task for Robustness and Accuracy of Supervised Models Submitted to Neurips2021 To
Machine Learning Model to predict the payment date of an invoice when it gets created in the system.
Payment-Date-Prediction Machine Learning Model to predict the payment date of an invoice when it gets created in the system.
darts is a Python library for easy manipulation and forecasting of time series.
A python library for easy manipulation and forecasting of time series.
VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning
This is a release of our VIMPAC paper to illustrate the implementations. The pretrained checkpoints and scripts will be soon open-sourced in HuggingFace transformers.
Deep Learning for Natural Language Processing - Lectures 2021
This repository contains slides for the course "20-00-0947: Deep Learning for Natural Language Processing" (Technical University of Darmstadt, Summer term 2021).
DouZero is a reinforcement learning framework for DouDizhu - 斗地主AI
[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning | 斗地主AI
A Tool to scrape URLs for a given domain from wayback machine, Commoncrawl and OTX Alienvault
Mr_URL Mr.URL fetches known URLs for a given domain from Wayback Machine, Commoncrawl and OTX Alienvault. It also finds old versions of any given URL
Learning with Peter Norvig's lis.py interpreter
Learning with lis.py This repository contains variations of Peter Norvig's lis.py interpreter for a subset of Scheme, described in (How to Write a (Li
Demo project for real time anomaly detection using kafka and python
kafkaml-anomaly-detection Project for real time anomaly detection using kafka and python It's assumed that zookeeper and kafka are running in the loca
graph learning code for ogb
The final code for OGB Installation Requirements: ogb=1.3.1 torch=1.7.0 torch-geometric=1.7.0 torch-scatter=2.0.6 torch-sparse=0.6.9 Baseline models T
Python code for "Machine learning: a probabilistic perspective" (2nd edition)
Python code for "Machine learning: a probabilistic perspective" (2nd edition)
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, scikit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio, video, etc.) and machine learning tasks (classification, object detection, speech recognition, generation, certification, etc.).
Jina allows you to build deep learning-powered search-as-a-service in just minutes
Cloud-native neural search framework for any kind of data
In this repository, I have developed an end to end Automatic speech recognition project. I have developed the neural network model for automatic speech recognition with PyTorch and used MLflow to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.
End to End Automatic Speech Recognition In this repository, I have developed an end to end Automatic speech recognition project. I have developed the
This websocket program is for data transmission between server and client. Data transmission is for Federated Learning in Edge computing environment.
websocket-for-data-transmission This websocket program is for data transmission between server and client. Data transmission is for Federated Learning
This repository contains the code for the paper "SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks"
SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks (CVPR 2021 Oral) This repository contains the official PyTorch implementation
An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.
An integration of several popular automatic augmentation methods, including OHL (Online Hyper-Parameter Learning for Auto-Augmentation Strategy) and AWS (Improving Auto Augment via Augmentation Wise Weight Sharing) by Sensetime Research.
This repository is an open-source implementation of the ICRA 2021 paper: Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling.
Locus This repository is an open-source implementation of the ICRA 2021 paper: Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order
[ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang
Graph Contrastive Learning Automated PyTorch implementation for Graph Contrastive Learning Automated [talk] [poster] [appendix] Yuning You, Tianlong C
[ICML 2021] “ Self-Damaging Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang
Self-Damaging Contrastive Learning Introduction The recent breakthrough achieved by contrastive learning accelerates the pace for deploying unsupervis
[CVPR 21] Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2021.
Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdhury, Yongxin Yan
Official NumPy Implementation of Deep Networks from the Principle of Rate Reduction (2021)
Deep Networks from the Principle of Rate Reduction This repository is the official NumPy implementation of the paper Deep Networks from the Principle
ML Optimizers from scratch using JAX
Toy implementations of some popular ML optimizers using Python/JAX
Markup is an online annotation tool that can be used to transform unstructured documents into structured formats for NLP and ML tasks, such as named-entity recognition. Markup learns as you annotate in order to predict and suggest complex annotations. Markup also provides integrated access to existing and custom ontologies, enabling the prediction and suggestion of ontology mappings based on the text you're annotating.
Markup is an online annotation tool that can be used to transform unstructured documents into structured formats for NLP and ML tasks, such as named-entity recognition. Markup learns as you annotate in order to predict and suggest complex annotations. Markup also provides integrated access to existing and custom ontologies, enabling the prediction and suggestion of ontology mappings based on the text you're annotating.