R codes for data generation and visualizations are in the folder simulation.
R codes fo source data selection an visualizations are in the folder experiment_CA.
Dependencies: One can use the docker image xinranmiao/transfer_hospital_v4:v0 created by Dockerfile. Python codes are in the folder experiment_camelyon.
SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win
Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent
Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu
Plan-then-Generate: Controlled Data-to-Text Generation via Planning Authors: Yixuan Su, David Vandyke, Sihui Wang, Yimai Fang, and Nigel Collier Code
SeqFormer: a Frustratingly Simple Model for Video Instance Segmentation SeqFormer SeqFormer: a Frustratingly Simple Model for Video Instance Segmentat
curriculum A comprehensive and up-to-date developer education platform for Urbit. This project organizes developer capabilities into a hierarchy of co
Learning the Best Pooling Strategy for Visual Semantic Embedding Official PyTorch implementation of the paper Learning the Best Pooling Strategy for V
BBB Face Recognizer Face recognition system using MTCNN, FACENET, SVM and FAST API to track participants of Big Brother Brasil in real time. Instalati
Online Pseudo Label Generation by Hierarchical Cluster Dynamics for Adaptive Person Re-identification
KOALA KOALA, the Kilofibre Optical AAT Lenslet Array, is a wide-field, high efficiency, integral field unit used by the AAOmega spectrograph on the 3.
Reference-based Video Super-Resolution (RefVSR) Official PyTorch Implementation of the CVPR 2022 Paper Project | arXiv | RealMCVSR Dataset This repo c
Self-Normalizing Networks Tutorials and implementations for "Self-normalizing networks"(SNNs) as suggested by Klambauer et al. (arXiv pre-print). Vers
Code for the ToeplitzLDA classifier proposed in here. The classifier conforms sklearn and can be used as a drop-in replacement for other LDA classifiers. For in-depth usage refer to the learning from
Compact Bilinear Pooling for PyTorch. This repository has a pure Python implementation of Compact Bilinear Pooling and Count Sketch for PyTorch. This
Single Image Depth Prediction with Wavelet Decomposition Michaël Ramamonjisoa, Michael Firman, Jamie Watson, Vincent Lepetit and Daniyar Turmukhambeto
Piggyback: https://arxiv.org/abs/1801.06519 Pretrained masks and backbones are available here: https://uofi.box.com/s/c5kixsvtrghu9yj51yb1oe853ltdfz4q
tisane Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships TL;DR: Analysts can use Tisane to author gener
Improving Deep Network Debuggability via Sparse Decision Layers This repository contains the code for our paper: Leveraging Sparse Linear Layers for D
Geometry Processing with Neural Fields Pytorch implementation for the NeurIPS 2021 paper: Geometry Processing with Neural Fields Guandao Yang, Serge B
Stochastic Normalizing Flows We introduce stochasticity in Boltzmann-generating flows. Normalizing flows are exact-probability generative models that
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