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Saraswati Soedarmadji

4 accepted papers

2025

Population Transformer: Learning Population-level Representations of Neural Activity

ICLR 2025oral

We present a self-supervised framework that learns population-level codes for arbitrary ensembles of neural recordings at scale. We address key challenges in scaling models with neural time-series data, namely, sparse and variable electrode distribution across subjects and datasets. The Population T…

2024

Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systems

CoRL 2024poster

Learning to move is a primary goal for animals and robots, where ensuring safety is often important when optimizing control policies on the embodied systems. For complex tasks such as the control of human or humanoid control, the high-dimensional parameter space adds complexity to the safe optimizat…

Cited by 0SourceScholar
2024

Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes

NeurIPS 2024poster

Bayesian optimization is an effective technique for black-box optimization, but its applicability is typically limited to low-dimensional and small-budget problems due to the cubic complexity of computing the Gaussian process (GP) surrogate. While various approximate GP models have been employed to…

2024

Semantics from Space: Satellite-Guided Thermal Semantic Segmentation Annotation for Aerial Field Robots

IROS 2024poster

We present a new method to automatically generate semantic segmentation annotations for thermal imagery captured from an aerial vehicle by utilizing satellite-derived data products alongside onboard global positioning and attitude estimates. This new capability overcomes the challenge of developing…

Cited by 3SourcecodeScholar