LLMMaps -- A Visual Metaphor for Stratified Evaluation of Large Language Models

1 code implementation • 2 Apr 2023 • Patrik Puchert, Poonam Poonam, Christian van Onzenoodt, Timo Ropinski

To support such stratified evaluations, we propose LLMMaps as a novel visualization technique that enables users to evaluate LLMs' performance with respect to Q&A datasets.

A3GC-IP: Attention-Oriented Adjacency Adaptive Recurrent Graph Convolutions for Human Pose Estimation from Sparse Inertial Measurements

no code implementations • 23 Jul 2021 • Patrik Puchert, Timo Ropinski

Conventional methods for human pose estimation either require a high degree of instrumentation, by relying on many inertial measurement units (IMUs), or constraint the recording space, by relying on extrinsic cameras.

Data Augmentation Graph Learning +1

Data-driven deep density estimation

1 code implementation • 23 Jul 2021 • Patrik Puchert, Pedro Hermosilla, Tobias Ritschel, Timo Ropinski

Density estimation plays a crucial role in many data analysis tasks, as it infers a continuous probability density function (PDF) from discrete samples.

Density Estimation