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lizhaoliu's Projects

mixture-of-experts icon mixture-of-experts

PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538

mlc icon mlc

Multi label calssification - pytorch.

nlp-tutorial icon nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

readme icon readme

README文件语法解读,即Github Flavored Markdown语法介绍

revisiting_deep_metric_learning_pytorch icon revisiting_deep_metric_learning_pytorch

(ICML 2020) This repo contains code for our paper "Revisiting Training Strategies and Generalization Performance in Deep Metric Learning" (https://arxiv.org/abs/2002.08473) to facilitate consistent research in the field of Deep Metric Learning.

salsanext icon salsanext

Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving

sphericalembedding icon sphericalembedding

official pytorch implementation of "Deep Metric Learning with Spherical Embedding", NeurIPS 2020

spotnet icon spotnet

Repository for the paper SpotNet: Self-Attention Multi-Task Network for Object Detection

task-one icon task-one

Experiments task one: Four pytorch examples cover CNN and transformer.

taskonomy-sample-model-1 icon taskonomy-sample-model-1

Model, selected at random, from the training set of the paper "Taskonomy: Disentangling Task Transfer Learning"

tfvaegan icon tfvaegan

Official repository with Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification" (ECCV 2020)

torchcv icon torchcv

A PyTorch-Based Framework for Deep Learning in Computer Vision

tsp-ga icon tsp-ga

A Genetic Algorithm in Python for the Travelling Salesman Problem

uc-berkeley-cs188-assignments icon uc-berkeley-cs188-assignments

This repository contains solutions of some assignments of uc berkeley cs188. Detailed description for the assignments can be found in the following URL.

vision icon vision

Datasets, Transforms and Models specific to Computer Vision

xmuda icon xmuda

Cross-Modal Unsupervised Domain Adaptationfor 3D Semantic Segmentation

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