Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
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MVDoppler: Unleashing the Power of Multi-View Doppler for MicroMotion-Based Gait Classification
Neural Information Processing Systems
Doppler-based systems are capable of measuring micro-motions of targets remotely and with very high precision.
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Norm-guided latent space exploration for text-to-image generation
Neural Information Processing Systems
They map random samples (seeds) from a high-dimensional space, conditioned on a user-provided text prompt, to a corresponding image.
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Residual Alignment: Uncovering the Mechanisms of Residual Networks
Neural Information Processing Systems
C is the number of classes; and (RA4) top singular values of Residual Jacobians scale inversely with depth.
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Masked Image Residual Learning for Scaling Deeper Vision Transformers
Neural Information Processing Systems
Deeper Vision Transformers (ViTs) are more challenging to train.
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