77 citations · 144 across the 7 of their papers we have counts for
8 papers
MAEEG: Masked Auto-encoder for EEG Representation Learning
Hsiang-Yun Sherry Chien, Hanlin Goh, Christopher M. Sandino +1
Decoding information from bio-signals such as EEG, using machine learning has been a challenge due to the small data-sets and difficulty to obtain labels. We propose a reconstructi…
Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents
Yao-Hung Hubert Tsai, Hanlin Goh, Ali Farhadi +1
The perception system in personalized mobile agents requires developing indoor scene understanding models, which can understand 3D geometries, capture objectiveness, analyze human…
Implicit Acceleration and Feature Learning in Infinitely Wide Neural Networks with Bottlenecks
Etai Littwin, Omid Saremi, Shuangfei Zhai +4
We analyze the learning dynamics of infinitely wide neural networks with a finite sized bottle-neck. Unlike the neural tangent kernel limit, a bottleneck in an otherwise infinite w…
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
Yue Wu, Shuangfei Zhai, Nitish Srivastava +4
Offline Reinforcement Learning promises to learn effective policies from previously-collected, static datasets without the need for exploration. However, existing Q-learning and ac…
An Attention Free Transformer
Shuangfei Zhai, Walter Talbott, Nitish Srivastava +4
We introduce Attention Free Transformer (AFT), an efficient variant of Transformers that eliminates the need for dot product self attention. In an AFT layer, the key and value are…
Subject-Aware Contrastive Learning for Biosignals
Joseph Y. Cheng, Hanlin Goh, Kaan Dogrusoz +2
Datasets for biosignals, such as electroencephalogram (EEG) and electrocardiogram (ECG), often have noisy labels and have limited number of subjects (<100). To handle these challen…