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Code for "Diversity can be Transferred: Output Diversification for White- and Black-box Attacks"
Output Diversified Sampling (ODS) This is the github repository for the NeurIPS 2020 paper "Diversity can be Transferred: Output Diversification for W
Fast, Attemptable Route Planner for Navigation in Known and Unknown Environments
FAR Planner uses a dynamically updated visibility graph for fast replanning. The planner models the environment with polygons and builds a global visi
A scientific and useful toolbox, which contains practical and effective long-tail related tricks with extensive experimental results
Bag of tricks for long-tailed visual recognition with deep convolutional neural networks This repository is the official PyTorch implementation of AAA
using STGCN to achieve egg classification task
EEG Classification The task requires us to classify electroencephalography(EEG) into six categories, including human body, human face, animal body,
Publication describing 3 ML examples at NSLS-II and interfacing into Bluesky
Machine learning enabling high-throughput and remote operations at large-scale user facilities. Overview This repository contains the source code and
This repository introduces a short project about Transfer Learning for Classification of MRI Images.
Transfer Learning for MRI Images Classification This repository introduces a short project made during my stay at Neuromatch Summer School 2021. This
TargetAllDomainObjects - A python wrapper to run a command on against all users/computers/DCs of a Windows Domain
TargetAllDomainObjects A python wrapper to run a command on against all users/co
Official implementation of Protected Attribute Suppression System, ICCV 2021
Official implementation of Protected Attribute Suppression System, ICCV 2021
PyTorch framework, for reproducing experiments from the paper Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu
Using CNN to mimic the driver based on training data from Torcs
Behavioural-Cloning-in-autonomous-driving Using CNN to mimic the driver based on training data from Torcs. Approach First, the data was collected from
Implementation of a Transformer that Ponders, using the scheme from the PonderNet paper
Ponder(ing) Transformer Implementation of a Transformer that learns to adapt the number of computational steps it takes depending on the difficulty of
A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows"
OutliersSlidingWindows A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows" Dataset generatio
Learning Correspondence from the Cycle-consistency of Time (CVPR 2019)
TimeCycle Code for Learning Correspondence from the Cycle-consistency of Time (CVPR 2019, Oral). The code is developed based on the PyTorch framework,
Implicit Graph Neural Networks
Implicit Graph Neural Networks This repository is the official PyTorch implementation of "Implicit Graph Neural Networks". Fangda Gu*, Heng Chang*, We
Learning the Beauty in Songs: Neural Singing Voice Beautifier; ACL 2022 (Main conference); Official code
Learning the Beauty in Songs: Neural Singing Voice Beautifier Jinglin Liu, Chengxi Li, Yi Ren, Zhiying Zhu, Zhou Zhao Zhejiang University ACL 2022 Mai
TorchXRayVision: A library of chest X-ray datasets and models.
torchxrayvision A library for chest X-ray datasets and models. Including pre-trained models. ( 🎬 promo video about the project) Motivation: While the
PyTorch Implementation of Sparse DETR
Sparse DETR By Byungseok Roh*, Jaewoong Shin*, Wuhyun Shin*, and Saehoon Kim at Kakao Brain. (*: Equal contribution) This repository is an official im
RRL: Resnet as representation for Reinforcement Learning
Resnet as representation for Reinforcement Learning (RRL) is a simple yet effective approach for training behaviors directly from visual inputs. We demonstrate that features learned by standard image
Deal or No Deal? End-to-End Learning for Negotiation Dialogues
Introduction This is a PyTorch implementation of the following research papers: (1) Hierarchical Text Generation and Planning for Strategic Dialogue (
Pytorch implementation of MLP-Mixer with loading pre-trained models.
MLP-Mixer-Pytorch PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision with the function of loading official ImageNet pre-trained p