[NeurIPS 2024 Best Paper][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-simple, user-friendly yet state-of-the-art* codebase for autoregressive image generation!

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning

深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)

This repository contains all the papers accepted in top conference of computer vision, with convenience to search related papers.

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

This repository is a paper digest of recent advances in collaborative / cooperative / multi-agent perception for V2I / V2V / V2X autonomous driving scenario.

Fetch Academic Research Papers from different sources

Code for our NeurIPS 2022 paper

multilspy is a lsp client library in Python intended to be used to build applications around language servers.

A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).

📚 List of Top-tier Conference Papers on Reinforcement Learning (RL)，including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.

This repository is a paper digest of Transformer-related approaches in visual tracking tasks.

Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)

A vue-based project page template for academic papers. (in development) https://junyaohu.github.io/academic-project-page-template-vue

Code and Data artifact for NeurIPS 2023 paper - "Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context". `multispy` is a lsp client library in Python intended to be used to build applications around language servers.

[NeurIPS 2021] Galerkin Transformer: a linear attention without softmax for Partial Differential Equations

[NeurIPS 2023] A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting

Official PyTorch implementation of TSDiff models presented in the NeurIPS 2023 paper "Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting"

Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement (NeurIPS 2020)