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  • ⚽ Hi, I’m Ruochen Li
  • 👀 I’m interested in Deep Learning and Machine Learning
  • 🌱 I’m currently interested in Graph Neural Networks (GNNs) and Time Series analysis
  • 📫 How to reach me: [email protected]

Ruochen Li's Projects

efficient-ai-backbones icon efficient-ai-backbones

Efficient AI Backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.

eigentrajectory icon eigentrajectory

Official Code for "EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecasting (ICCV 2023)"

eth-ucy- icon eth-ucy-

Introductory tutorials for trajectory generation.

fairseq icon fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

forecast-mae icon forecast-mae

[ICCV'2023] Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoders

gmvae icon gmvae

Implementation of Gaussian Mixture Variational Autoencoder (GMVAE) for Unsupervised Clustering

gpgraph icon gpgraph

Official Code for "Learning Pedestrian Group Representations for Multi-modal Trajectory Prediction (ECCV 2022)"

graphtern icon graphtern

Official Code for "A Set of Control Points Conditioned Pedestrian Trajectory Prediction (AAAI 2023)"

hivt icon hivt

[CVPR 2022] HiVT: Hierarchical Vector Transformer for Multi-Agent Motion Prediction

howtocook icon howtocook

程序员在家做饭方法指南。Programmer's guide about how to cook at home (Chinese only).

it_takes_two icon it_takes_two

This repository contains all the codes share with a nice person~

lanegcn_ref icon lanegcn_ref

An implementation of LaneGCN (Learning Lane Graph Representations for Motion Forecasting)

ltsf-linear-aaai-2023-oral- icon ltsf-linear-aaai-2023-oral-

This is the official implementation for AAAI-23 Oral paper "Are Transformers Effective for Time Series Forecasting?"

memonet icon memonet

Official PyTorch code for "Remember Intentions: Retrospective-Memory-based Trajectory Prediction".

neuralforecast icon neuralforecast

Scalable and user friendly neural :brain: forecasting algorithms.

p2t icon p2t

Code for "Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans" https://arxiv.org/abs/2001.00735

powerbev icon powerbev

POWERBEV, a novel and elegant vision-based end-to-end framework that only consists of 2D convolutional layers to perform perception and forecasting of multiple objects in BEVs.

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