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Trilinear Attention Sampling Network for Fine-grained Image Recognition

Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.

W3C Strategic Highlights September 2019 This report was prepared for the September 2019 W3C Advisory Committee Meeting (W3C Member link). See the accompanying W3C Fact Sheet — September 2019. For the previous edition, see the April 2019 W3C Strategic Highlights. For future editions of this repo... Read more

Official repository for paper "Attention-based Point Cloud Edge Sampling" (APES), Highlight@CVPR 2023

Official implementation of the paper "Improving Sample Quality of Diffusion Models Using Self-Attention Guidance" (ICCV`23)

This repo provides the processed samples of the manuscript "MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-head Transformer with Convolution-augmented Joint Self-Attentions", which was submitted to ICASSP 2023.

This Python package enables the training and inference of deep learning models for very large data, such as megapixel images, using attention-sampling

An ANN is a model based on a collection of connected units or nodes called "artificial neurons", which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artific... Read more

[EVA ICLR'23; LARA ICML'22] Efficient attention mechanisms via control variates, random features, and importance sampling

Code for our paper "Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition"