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The fastest way to create an HTML app
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
A maritime dataset for object detection. The dataset is a collection of images captured from live video feeds recorded across various port based areas of Germany. These images contain multiple inst…
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Updated Oct 19, 2023
TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's …
Dir-GNN is a machine learning model that enables learning on directed graphs.
A comprehensive survey on the time series domains
Code for our CIKM'22 paper Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting.
tsl: a PyTorch library for processing spatiotemporal data.
A principled instruction benchmark on formulating effective queries and prompts for large language models (LLMs). Our paper: https://arxiv.org/abs/2312.16171
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
[CVPR 2024 - Oral, Best Paper Award Candidate] Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
Inference Vision Transformer (ViT) in plain C/C++ with ggml
A repository for code accompanying the manuscript 'An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series' (published at TNNLS)
Battle of the Leakage Detection and Isolation Methods (BattLeDIM 2020)
llama and other large language models on iOS and MacOS offline using GGML library.
A 1D implementation of a deformable convolutional layer in PyTorch with a few tricks.
[ICLR 2023 Spotlight] Vision Transformer Adapter for Dense Predictions
[CVPR 2023 Highlight] InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
DAGs with NO TEARS: Continuous Optimization for Structure Learning
Must-read papers on graph neural networks (GNN)
An AI-app that allows you to upload a PDF and ask questions about it. It uses OpenAI's LLMs to generate a response.
A collection of papers on the topic of ``Computer Vision in the Wild (CVinW)''
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Hydra is a framework for elegantly configuring complex applications