124 citations · 490 across the 52 of their papers we have counts for
12 papers · 1 filter
Flowing from Reasoning to Motion: Learning 3D Hand Trajectory Prediction from Egocentric Human Interaction Videos
Mingfei Chen, Yifan Wang, Zhengqin Li +10
Prior works on 3D hand trajectory prediction are constrained by datasets that decouple motion from semantic supervision and by models that weakly link reasoning and action. To addr…
Advantages of Broadband Metalenses for Generalizable Image Classification
Yubo Zhang, Johannes Fröch, Jinlin Xiang +6
Optical neural networks (ONNs) are gaining increasing attention to accelerate machine learning tasks. In particular, static meta-optical encoders designed for task-specific pre-pro…
Neural Tangent Knowledge Distillation for Optical Convolutional Networks
Jinlin Xiang, Minho Choi, Yubo Zhang +3
Hybrid Optical Neural Networks (ONNs, typically consisting of an optical frontend and a digital backend) offer an energy-efficient alternative to fully digital deep networks for re…
SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding
Trung Le, Hao Fang, Jingyuan Li +5
Intracortical Brain-Computer Interfaces (iBCI) aim to decode behavior from neural population activity, enabling individuals with motor impairments to regain motor functions and com…
KPFlow: An Operator Perspective on Dynamic Collapse Under Gradient Descent Training of Recurrent Networks
James Hazelden, Laura Driscoll, Eli Shlizerman +1
Gradient Descent (GD) and its variants are the primary tool for enabling efficient training of recurrent dynamical systems such as Recurrent Neural Networks (RNNs), Neural ODEs and…
Hyperpruning: Efficient Search through Pruned Variants of Recurrent Neural Networks Leveraging Lyapunov Spectrum
Caleb Zheng, Eli Shlizerman
A variety of pruning methods have been introduced for over-parameterized Recurrent Neural Networks to improve efficiency in terms of power consumption and storage utilization. Thes…