Loss functions and constraints improve sea surface height prediction

In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or ...
IEEE

Graphmad: Graph Mixup for Data Augmentation Using Data-Driven Convex Clustering

Abstract: We develop a novel data-driven nonlinear mixup mechanism for graph data augmentation and present different mixup functions for sample pairs and their labels. Mixup is a data augmentation ...
GitHub

NVIDIA Context Aware RAG

Context Aware RAG is a flexible library designed to seamlessly integrate into existing data processing workflows to build customized data ingestion and retrieval (RAG) pipelines. With Context Aware ...
GitHub

Motion Planning around Obstacles with Convex Optimization

This repository contains the code to reproduce the examples in the paper Motion Planning around Obstacles with Convex Optimization by Tobia Marcucci, Mark Petersen, David von Wrangel, and Russ Tedrake ...
Microsoft

Robust Algorithms for Online Convex Problems via Primal-Dual

Primal-dual methods in online optimization give several of the state-of-the art results in both of the most common models: adversarial and stochastic/random order. Here we try to provide a more ...
IEEE

Planning Shorter Paths in Graphs of Convex Sets by Undistorting Parametrized Configuration Spaces

Abstract: Optimization based motion planning provides a useful modeling framework through various costs and constraints. Using Graph of Convex Sets (GCS) for trajectory optimization gives guarantees ...