mc-o
Follow
Stars
An end-to-end pipeline for enriching and analyzing GPS trajectories to understand cycling behavior and environment.
This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the …
Multivariate Time Series Transformer, public version
A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."
A machine learning compiler for GPUs, CPUs, and ML accelerators
Resources for the practical classes of UCL COMP0189 Applied Artificial Intelligence
[IJCAI-24] Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting
Video descriptions of research papers relating to foundation models and scaling
A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)
Advanced object tracking system in Turkey Live CCTV footages.
ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
code for paper "Graph Structure of Neural Networks"
Carbon Language's main repository: documents, design, implementation, and related tools. (NOTE: Carbon Language is experimental; see README)
Representing robots as graphs for reinforcement-learning in PyBullet locomotion environments.
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
Code for "Neural 3D Reconstruction in the Wild", SIGGRAPH 2022 (Conference Proceedings)