Quality-Diversity Generative Sampling for Learning with Synthetic Data

1 code implementation • 22 Dec 2023 • Allen Chang, Matthew C. Fontaine, Serena Booth, Maja J. Matarić, Stefanos Nikolaidis

QDGS is a model-agnostic framework that uses prompt guidance to optimize a quality objective across measures of diversity for synthetically generated data, without fine-tuning the generative model.

Fairness

Multimodal Speech Recognition for Language-Guided Embodied Agents

1 code implementation • 27 Feb 2023 • Allen Chang, Xiaoyuan Zhu, Aarav Monga, Seoho Ahn, Tejas Srinivasan, Jesse Thomason

Benchmarks for language-guided embodied agents typically assume text-based instructions, but deployed agents will encounter spoken instructions.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Removing Radio Frequency Interference from Auroral Kilometric Radiation with Stacked Autoencoders

1 code implementation • 24 Oct 2022 • Allen Chang, Mary Knapp, James LaBelle, John Swoboda, Ryan Volz, Philip J. Erickson

The framework for simulating AKR, training DAARE, and employing DAARE can be accessed at github. com/Cylumn/daare.

Astronomy Denoising +1

Evaluating Temporal Patterns in Applied Infant Affect Recognition

no code implementations • 7 Sep 2022 • Allen Chang, Lauren Klein, Marcelo R. Rosales, Weiyang Deng, Beth A. Smith, Maja J. Matarić

Next, we conducted an in-depth analysis of our best-performing models to evaluate how performance changed over time as the models encountered missing data and changing infant affect.

Learning Partially Observable Deterministic Action Models

no code implementations • 15 Jan 2014 • Eyal Amir, Allen Chang

Our algorithms take sequences of partial observations over time as input, and output deterministic action models that could have lead to those observations.

Partially Observable Reinforcement Learning reinforcement-learning +1