Neural Networks

Simple Hardware-Efficient Long Convolutions for Sequence Modeling ICML 2023 Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth ICLR 2023 Simpler neural networks prefer subregular languages EMNLP 2023 Simplicial Hopfield networks ICLR 2023 Simplicity Bias in 1-Hidden Layer Neural Networks NeurIPS 2023 Simplified State Space Layers for Sequence Modeling ICLR 2023 Simulating Network Paths with Recurrent Buffering Units AAAI 2023 Simultaneous Acquisition of High Quality RGB Image and Polarization Information Using a Sparse Polarization Sensor WACV 2023 Simultaneous embedding of multiple attractor manifolds in a recurrent neural network using constrained gradient optimization NeurIPS 2023 Single Image Super-resolution Based On Non-subsampled Shearlet Transform ACML 2023 Single Image Super-Resolution via a Dual Interactive Implicit Neural Network WACV 2023 SinGRAF: Learning a 3D Generative Radiance Field for a Single Scene CVPR 2023 Singular Value Representation: A New Graph Perspective On Neural Networks AISTATS 2023 SIUNet: Sparsity Invariant U-Net for Edge-Aware Depth Completion WACV 2023 Skinned Motion Retargeting With Residual Perception of Motion Semantics & Geometry CVPR 2023 SLACK: Stable Learning of Augmentations With Cold-Start and KL Regularization CVPR 2023 SLI-pSp: Injecting Multi-Scale Spatial Layout in pSp WACV 2023 SLNet: A Spectrogram Learning Neural Network for Deep Wireless Sensing NSDI 2023 Slow and Weak Attractor Computation Embedded in Fast and Strong E-I Balanced Neural Dynamics NeurIPS 2023 Smooth, exact rotational symmetrization for deep learning on point clouds NeurIPS 2023 SMPConv: Self-Moving Point Representations for Continuous Convolution CVPR 2023 SolderNet: Towards Trustworthy Visual Inspection of Solder Joints in Electronics Manufacturing Using Explainable Artificial Intelligence AAAI 2023 Sparse Activations for Interpretable Disease Grading MIDL 2023 Sparse Deep Learning for Time Series Data: Theory and Applications NeurIPS 2023 Sparse Mixture-of-Experts are Domain Generalizable Learners ICLR 2023