37 docs tagged with "Foundation-AI"

A curated ICICLE benchmark for evaluating the performance of pre-trained models and fostering the development of adaptation algorithms in the camera trap domain.

Explanation for Camera Trap Benchmark. ICICLE benchmark for camera trap image analysis with adaptive learning capabilities.

How-To Guides for Camera Trap Benchmark. ICICLE benchmark for camera trap image analysis with adaptive learning capabilities.

ICICLE benchmark for camera trap image analysis with adaptive learning capabilities.

Explanation for CAN Benchmark. A curated ICICLE benchmark for evaluating the performance of pre-trained models and fostering the development of adaptation…

How-To Guides for CAN Benchmark. A curated ICICLE benchmark for evaluating the performance of pre-trained models and fostering the development of adaptation…

This repository contains tools and instructions for reproducing the experiments in the paper

Data

The Forte library provides robust out-of-distribution (OOD) detection capabilities through the ForteOODDetector class. The core algorithm is built on the principle of Finding Outliers using Representation Typicality Estimation, which:

How-To Guides for Forte. The Forte library provides robust out-of-distribution (OOD) detection capabilities through the ForteOODDetector class.

Tutorials for Forte. The Forte library provides robust out-of-distribution (OOD) detection capabilities through the ForteOODDetector class.

How-To Guides for ICICLE Foodshed Parser. This repository contains tools and instructions for reproducing the experiments in the paper

SDK to interact with the ICICLE Model & Data Playgrounds

Explanation for ICICLE-Playgrounds. ICICLE Playgrounds is a Python SDK designed for working with AI plug-n-play frameworks powered by Tapis Workflows.

How To Guides for ICICLE-Playgrounds. ICICLE Playgrounds is a Python SDK designed for working with AI plug-n-play frameworks powered by Tapis Workflows.

Tutorial for ICICLE-Playgrounds. ICICLE Playgrounds is a Python SDK designed for working with AI plug-n-play frameworks powered by Tapis Workflows.

Lessons and Insights from a Unifying Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition

How-To Guides for PEFT Vision. Parameter-efficient fine-tuning (PEFT) has attracted significant attention lately due to the increasing size of pre-trained…

How-To Guides for Plug-and-Play Speech Interfaces v0.2.

Speech is the new essential fuel for human-computer interaction. With the current trend of

How-To Guides for Plug-N-Play Speech Interfaces v1.0. Speech is the new essential fuel for human-computer interaction.

Region2vec: Community Detection on Spatial Networks Using Graph Embedding with Node Attributes and Spatial Interactions

How-To Guide for Region2vec. Region2vec: Community Detection on Spatial Networks Using Graph Embedding with Node Attributes and Spatial Interactions

Language agents for data-driven scientific discovery tasks. The agent features the self-debug mechanism and shows the best performance on ScienceAgentBench.

Explanation for Science Agents v1.0. Language agents for data-driven scientific discovery tasks.

How-To Guides for Science Agents v1.0. Language agents for data-driven scientific discovery tasks.

ScienceAgent Interface provides a web interface for conducting data-driven scientific tasks using ScienceAgent. The interface connects to a Python backend which allows users to execute generated programs in an isolated Docker environment and view the results.

How-To Guides for ScienceAgent Interface. ScienceAgent Interface provides a web interface for conducting data-driven scientific tasks using ScienceAgent.

An AI-driven educational framework that integrates automated curriculum generation with an end-to-end computer vision pipeline, enabling learning for high school and undergraduate students combining domain agnostic datasets with machine learning and AI concepts.

Tutorials for Smart Curriculum Designer. An AI-driven educational framework that integrates automated curriculum generation with an end-to-end computer vision…

We present a species classification model that utilizes heterogeneous image contexts organized in a multimodal knowledge graph. The multimodal knowledge graph may include diverse forms of heterogeneous contexts that pertain to different modalities, such as numerical information for locations and time, categorical data for species/taxon IDs, and visual content such as images.

How-To Guides for Species Classification using Multimodal Heterogeneous Context. We present a species classification model that utilizes heterogeneous image…

GitHub Repo

A Hugging Face custom pipeline using Transformers model for county-level corn yield estimation using multi-temporal weather observations and static soil properties.

Explanation for Yield Estimation. A Hugging Face custom pipeline using Transformers model for county-level corn yield estimation using multi-temporal weather…

How-To Guides for Yield Estimation. A Hugging Face custom pipeline using Transformers model for county-level corn yield estimation using multi-temporal…

Tutorials for Yield Estimation. A Hugging Face custom pipeline using Transformers model for county-level corn yield estimation using multi-temporal weather…