1 citations · 1 across the 2 of their papers we have counts for
5 papers
Continuous Conditioning of VLAs with Augmenting EMG and Visual Task Descriptors
Edward W. Staley, Connor O. Pyles, Rahul Hingorani +5
Vision-Language-Action (VLA) models rely strongly on language for describing task information, despite having multimodal inputs. We hypothesize that other modalities in the state s…
A Statistical Mixture-of-Experts Framework for EMG Artifact Removal in EEG: Empirical Insights and a Proof-of-Concept Application
Benjamin J. Choi, Griffin Milsap, Clara A. Scholl +2
Effective control of neural interfaces is limited by poor signal quality. While neural network-based electroencephalography (EEG) denoising methods for electromyogenic (EMG) artifa…
StARS DCM: A Sleep Stage-Decoding Forehead EEG Patch for Real-time Modulation of Sleep Physiology
William G. Coon, Preston Peranich, Griffin Milsap
The System to Augment Restorative Sleep (StARS) is a modular hardware/software platform designed for real-time sleep monitoring and intervention. Utilizing the compact DCM biosigna…
EEG Foundation Models for BCI Learn Diverse Features of Electrophysiology
Mattson Ogg, Rahul Hingorani, Diego Luna +3
Brain computer interface (BCI) research, as well as increasing portions of the field of neuroscience, have found success deploying large-scale artificial intelligence (AI) pre-trai…
Targeted Adversarial Denoising Autoencoders (TADA) for Neural Time Series Filtration
Benjamin J. Choi, Griffin Milsap, Clara A. Scholl +2
Current machine learning (ML)-based algorithms for filtering electroencephalography (EEG) time series data face challenges related to cumbersome training times, regularization, and…