192 Repositories
Python equivariant-representations Libraries
Improving Transferability of Representations via Augmentation-Aware Self-Supervision
Improving Transferability of Representations via Augmentation-Aware Self-Supervision Accepted to NeurIPS 2021 TL;DR: Learning augmentation-aware infor
Equivariant CNNs for the sphere and SO(3) implemented in PyTorch
Equivariant CNNs for the sphere and SO(3) implemented in PyTorch
Official implementation of the paper WAV2CLIP: LEARNING ROBUST AUDIO REPRESENTATIONS FROM CLIP
Wav2CLIP 🚧 WIP 🚧 Official implementation of the paper WAV2CLIP: LEARNING ROBUST AUDIO REPRESENTATIONS FROM CLIP 📄 🔗 Ho-Hsiang Wu, Prem Seetharaman
Improving Query Representations for DenseRetrieval with Pseudo Relevance Feedback:A Reproducibility Study.
APR The repo for the paper Improving Query Representations for DenseRetrieval with Pseudo Relevance Feedback:A Reproducibility Study. Environment setu
Official code for the paper Inverse Problems Leveraging Pre-trained Contrastive Representations.
The official code for the paper "Inverse Problems Leveraging Pre-trained Contrastive Representations" (to appear in NeurIPS 2021).
Public Implementation of ChIRo from "Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations"
Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations This directory contains the model architectures and experimental
PyTorch code of my WACV 2022 paper Improving Model Generalization by Agreement of Learned Representations from Data Augmentation
Improving Model Generalization by Agreement of Learned Representations from Data Augmentation (WACV 2022) Paper ArXiv Why it matters? When data augmen
Pytorch implementation of MixNMatch
MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation [Paper] Yuheng Li, Krishna Kumar Singh, Utkarsh Ojha, Yong Jae Le
A framework to train language models to learn invariant representations.
Invariant Language Modeling Implementation of the training for invariant language models. Motivation Modern pretrained language models are critical co
Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions
Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions Usage Clone the code to local. https://github.com/tanlab/MI
Learning Representations that Support Robust Transfer of Predictors
Transfer Risk Minimization (TRM) Code for Learning Representations that Support Robust Transfer of Predictors Prepare the Datasets Preprocess the Scen
Official code release for "Learned Spatial Representations for Few-shot Talking-Head Synthesis" ICCV 2021
Official code release for "Learned Spatial Representations for Few-shot Talking-Head Synthesis" ICCV 2021
Learning Fair Representations for Recommendation: A Graph-based Perspective, WWW2021
FairGo WWW2021 Learning Fair Representations for Recommendation: A Graph-based Perspective As a key application of artificial intelligence, recommende
Learning Facial Representations from the Cycle-consistency of Face (ICCV 2021)
Learning Facial Representations from the Cycle-consistency of Face (ICCV 2021) This repository contains the code for our ICCV2021 paper by Jia-Ren Cha
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations)
Graph Neural Networks with Learnable Structural and Positional Representations Source code for the paper "Graph Neural Networks with Learnable Structu
Efficient matrix representations for working with tabular data
Efficient matrix representations for working with tabular data
Code for generating the figures in the paper "Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views?"
Code for running simulations for the paper "Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Lin
ImageNet-CoG is a benchmark for concept generalization. It provides a full evaluation framework for pre-trained visual representations which measure how well they generalize to unseen concepts.
The ImageNet-CoG Benchmark Project Website Paper (arXiv) Code repository for the ImageNet-CoG Benchmark introduced in the paper "Concept Generalizatio
HyperCube: Implicit Field Representations of Voxelized 3D Models
HyperCube: Implicit Field Representations of Voxelized 3D Models Authors: Magdalena Proszewska, Marcin Mazur, Tomasz Trzcinski, Przemysław Spurek [Pap
PyTorch implementation for paper StARformer: Transformer with State-Action-Reward Representations.
StARformer This repository contains the PyTorch implementation for our paper titled StARformer: Transformer with State-Action-Reward Representations.
Permute Me Softly: Learning Soft Permutations for Graph Representations
Permute Me Softly: Learning Soft Permutations for Graph Representations
Code for the paper Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations (AKBC 2021).
Relation Prediction as an Auxiliary Training Objective for Knowledge Base Completion This repo provides the code for the paper Relation Prediction as
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
This repository contains the code for the CVPR 2021 paper "GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields"
GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields Project Page | Paper | Supplementary | Video | Slides | Blog | Talk If
An official reimplementation of the method described in the INTERSPEECH 2021 paper - Speech Resynthesis from Discrete Disentangled Self-Supervised Representations.
Speech Resynthesis from Discrete Disentangled Self-Supervised Representations Implementation of the method described in the Speech Resynthesis from Di
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
Poincaré Embeddings for Learning Hierarchical Representations PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations
Supervised Contrastive Learning for Downstream Optimized Sequence Representations
SupCL-Seq 📖 Supervised Contrastive Learning for Downstream Optimized Sequence representations (SupCS-Seq) accepted to be published in EMNLP 2021, ext
[EMNLP 2021] MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations
MuVER This repo contains the code and pre-trained model for our EMNLP 2021 paper: MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity
Source code for the paper "TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations"
TearingNet: Point Cloud Autoencoder to Learn Topology-Friendly Representations Created by Jiahao Pang, Duanshun Li, and Dong Tian from InterDigital In
Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"
Topographic Variational Autoencoder Paper: https://arxiv.org/abs/2109.01394 Getting Started Install requirements with Anaconda: conda env create -f en
Tensorflow 2 implementation of the paper: Learning and Evaluating Representations for Deep One-class Classification published at ICLR 2021
Deep Representation One-class Classification (DROC). This is not an officially supported Google product. Tensorflow 2 implementation of the paper: Lea
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors
You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors In this paper, we propose a novel local descriptor-based fra
[ICCV'21] Official implementation for the paper Social NCE: Contrastive Learning of Socially-aware Motion Representations
CrowdNav with Social-NCE This is an official implementation for the paper Social NCE: Contrastive Learning of Socially-aware Motion Representations by
[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
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
Code for Motion Representations for Articulated Animation paper
Motion Representations for Articulated Animation This repository contains the source code for the CVPR'2021 paper Motion Representations for Articulat
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
Geometric Vector Perceptron --- a rotation-equivariant GNN for learning from biomolecular structure
Geometric Vector Perceptron Code to accompany Learning from Protein Structure with Geometric Vector Perceptrons by B Jing, S Eismann, P Suriana, RJL T
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
Poincaré Embeddings for Learning Hierarchical Representations PyTorch implementation of Poincaré Embeddings for Learning Hierarchical Representations
Global Rhythm Style Transfer Without Text Transcriptions
Global Prosody Style Transfer Without Text Transcriptions This repository provides a PyTorch implementation of AutoPST, which enables unsupervised glo
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte
Global Rhythm Style Transfer Without Text Transcriptions
Global Prosody Style Transfer Without Text Transcriptions This repository provides a PyTorch implementation of AutoPST, which enables unsupervised glo
PyTorch implementation of paper: HPNet: Deep Primitive Segmentation Using Hybrid Representations.
HPNet This repository contains the PyTorch implementation of paper: HPNet: Deep Primitive Segmentation Using Hybrid Representations. Installation The
Here is the implementation of our paper S2VC: A Framework for Any-to-Any Voice Conversion with Self-Supervised Pretrained Representations.
S2VC Here is the implementation of our paper S2VC: A Framework for Any-to-Any Voice Conversion with Self-Supervised Pretrained Representations. In thi
Code release for BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images
BlockGAN Code release for BlockGAN: Learning 3D Object-aware Scene Representations from Unlabelled Images BlockGAN: Learning 3D Object-aware Scene Rep
[ACL 20] Probing Linguistic Features of Sentence-level Representations in Neural Relation Extraction
REval Table of Contents Introduction Overview Requirements Installation Probing Usage Citation License 🎓 Introduction REval is a simple framework for
A universal framework for learning timestamp-level representations of time series
TS2Vec This repository contains the official implementation for the paper Learning Timestamp-Level Representations for Time Series with Hierarchical C
Code for the paper "Implicit Representations of Meaning in Neural Language Models"
Implicit Representations of Meaning in Neural Language Models Preliminaries Create and set up a conda environment as follows: conda create -n state-pr
Code for "Learning Canonical Representations for Scene Graph to Image Generation", Herzig & Bar et al., ECCV2020
Learning Canonical Representations for Scene Graph to Image Generation (ECCV 2020) Roei Herzig*, Amir Bar*, Huijuan Xu, Gal Chechik, Trevor Darrell, A
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
Code to train models from "Paraphrastic Representations at Scale".
Paraphrastic Representations at Scale Code to train models from "Paraphrastic Representations at Scale". The code is written in Python 3.7 and require
Compositional and Parameter-Efficient Representations for Large Knowledge Graphs
NodePiece - Compositional and Parameter-Efficient Representations for Large Knowledge Graphs NodePiece is a "tokenizer" for reducing entity vocabulary
Pretraining Representations For Data-Efficient Reinforcement Learning
Pretraining Representations For Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Ch
Code for CVPR2021 paper 'Where and What? Examining Interpretable Disentangled Representations'.
PS-SC GAN This repository contains the main code for training a PS-SC GAN (a GAN implemented with the Perceptual Simplicity and Spatial Constriction c
LieTransformer: Equivariant Self-Attention for Lie Groups
LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant Self-At
Learning trajectory representations using self-supervision and programmatic supervision.
Trajectory Embedding for Behavior Analysis (TREBA) Implementation from the paper: Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Y
Code for the ACL2021 paper "Combining Static Word Embedding and Contextual Representations for Bilingual Lexicon Induction"
CSCBLI Code for our ACL Findings 2021 paper, "Combining Static Word Embedding and Contextual Representations for Bilingual Lexicon Induction". Require
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [2021]
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations This repo contains the Pytorch implementation of our paper: Revisit
To automate the generation and validation tests of COSE/CBOR Codes and it's base45/2D Code representations
To automate the generation and validation tests of COSE/CBOR Codes and it's base45/2D Code representations, a lot of data has to be collected to ensure the variance of the tests. This respository was established to collect a lot of different test data and related test cases of different member states in a standardized manner. Each member state can generate a folder in this section.
PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations This is the official PyTorch implementation
Conformer: Local Features Coupling Global Representations for Visual Recognition
Conformer: Local Features Coupling Global Representations for Visual Recognition (arxiv) This repository is built upon DeiT and timm Usage First, inst
Code for Learning Manifold Patch-Based Representations of Man-Made Shapes, in ICLR 2021.
LearningPatches | Webpage | Paper | Video Learning Manifold Patch-Based Representations of Man-Made Shapes Dmitriy Smirnov, Mikhail Bessmeltsev, Justi
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
CURL Rainbow Status: Archive (code is provided as-is, no updates expected) This is an implementation of CURL: Contrastive Unsupervised Representations
Deduplication is the task to combine different representations of the same real world entity.
Deduplication is the task to combine different representations of the same real world entity. This package implements deduplication using active learning. Active learning allows for rapid training without having to provide a large, manually labelled dataset.
A static analysis library for computing graph representations of Python programs suitable for use with graph neural networks.
python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu
Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks
This is the code associated with the paper Predicting Semantic Map Representations from Images with Pyramid Occupancy Networks, published at CVPR 2020.
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning
GenSen Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning Sandeep Subramanian, Adam Trischler, Yoshua B
Language-Agnostic SEntence Representations
LASER Language-Agnostic SEntence Representations LASER is a library to calculate and use multilingual sentence embeddings. NEWS 2019/11/08 CCMatrix is
Code for the paper "Unsupervised Contrastive Learning of Sound Event Representations", ICASSP 2021.
Unsupervised Contrastive Learning of Sound Event Representations This repository contains the code for the following paper. If you use this code or pa
Code for the paper: Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization (https://arxiv.org/abs/2002.11798)
Representation Robustness Evaluations Our implementation is based on code from MadryLab's robustness package and Devon Hjelm's Deep InfoMax. For all t
Vector Neurons: A General Framework for SO(3)-Equivariant Networks
Vector Neurons: A General Framework for SO(3)-Equivariant Networks Created by Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacc
Pytorch implementation of COIN, a framework for compression with implicit neural representations 🌸
COIN 🌟 This repo contains a Pytorch implementation of COIN: COmpression with Implicit Neural representations, including code to reproduce all experim
Proto-RL: Reinforcement Learning with Prototypical Representations
Proto-RL: Reinforcement Learning with Prototypical Representations This is a PyTorch implementation of Proto-RL from Reinforcement Learning with Proto
Code for Iso-Points: Optimizing Neural Implicit Surfaces with Hybrid Representations
Implementation for Iso-Points (CVPR 2021) Official code for paper Iso-Points: Optimizing Neural Implicit Surfaces with Hybrid Representations paper |
Official PyTorch implementation of Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations
Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations Zhenyu Jiang, Yifeng Zhu, Maxwell Svetlik, Kuan Fang, Yu
《LXMERT: Learning Cross-Modality Encoder Representations from Transformers》(EMNLP 2020)
The Most Important Thing. Our code is developed based on: LXMERT: Learning Cross-Modality Encoder Representations from Transformers
Learning Dense Representations of Phrases at Scale (Lee et al., 2020)
DensePhrases DensePhrases provides answers to your natural language questions from the entire Wikipedia in real-time. While it efficiently searches th
pip install antialiased-cnns to improve stability and accuracy
Antialiased CNNs [Project Page] [Paper] [Talk] Making Convolutional Networks Shift-Invariant Again Richard Zhang. In ICML, 2019. Quick & easy start Ru
Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed. KDD 2019.
gHHC Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, D
Official code of the paper "ReDet: A Rotation-equivariant Detector for Aerial Object Detection" (CVPR 2021)
ReDet: A Rotation-equivariant Detector for Aerial Object Detection ReDet: A Rotation-equivariant Detector for Aerial Object Detection (CVPR2021), Jiam
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)
Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O
Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch
Omninet - Pytorch Implementation of OmniNet, Omnidirectional Representations from Transformers, in Pytorch. The authors propose that we should be atte
EGNN - Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch
EGNN - Pytorch Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch. May be eventually used for Alphafold2 replication. This
Official pytorch implementation of paper "Image-to-image Translation via Hierarchical Style Disentanglement".
HiSD: Image-to-image Translation via Hierarchical Style Disentanglement Official pytorch implementation of paper "Image-to-image Translation
Implementation of E(n)-Transformer, which extends the ideas of Welling's E(n)-Equivariant Graph Neural Network to attention
E(n)-Equivariant Transformer (wip) Implementation of E(n)-Equivariant Transformer, which extends the ideas from Welling's E(n)-Equivariant G
Authors implementation of LieTransformer: Equivariant Self-Attention for Lie Groups
LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant self-at
GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
GAP-text2SQL: Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training Code and model from our AAAI 2021 paper
Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch.
SE3 Transformer - Pytorch Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. May be needed for replicating Alphafold2 resu
Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch
Lie Transformer - Pytorch (wip) Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch. Only the SE3 version will be present in thi