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aero-gnn

The official repository of "Towards Deep Attention in Graph Neural Networks: Problems and Remedies," published in ICML 2023.

astgcn-r-pytorch

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version

astgnn

This is a Pytorch implementation of ASTGNN. Now the corresponding paper is available online at https://ieeexplore.ieee.org/document/9346058.

bayesian-invariant-risk-minmization

This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.

catheartbeat

conformal_classification

Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

ddpm-ipa-protein-generation

Implementation of the DDPM + IPA (invariant point attention) for protein generation, as outlined in the paper "Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models"

diffusion_priors

Using pre-trained Diffusion models as priors for inference tasks

eecs_6998_e11

Repo for course project of EECS_6998_E11

eks

Ensembling and kalman smoothing for pose estimation

guided-diffusion

haotianxiang.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

lightning-pose

Accelerated pose estimation and tracking using semi-supervised convolutional networks.

multimodal_supercon

Multimodal SuperCon: Classifier for Drivers of Deforestation in Indonesia

personal_website

safegraph_baseline

secrete-recipe

segment-and-track-anything

An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) for key-frame segmentation and Associating Objects with Transformers (AOT) for efficient tracking and propagation purposes.

track-anything

Track-Anything is a flexible and interactive tool for video object tracking and segmentation, based on Segment Anything, XMem, and E2FGVI.

v-diffusion-jax

v objective diffusion inference code for JAX.

zin_official

This is the implementation for the NeurIPS 2022 paper: ZIN: When and How to Learn Invariance Without Environment Partition?