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.
Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching
Neural Information Processing Systems
Tweedie's formula, we show that we can perform gradient steps to sequentially optimize these objectives.
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Vript: A Video Is Worth Thousands of Words Dongjie Y ang
Neural Information Processing Systems
As a video has an additional temporal dimension, it contains more information than a single image.
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Geometric-A veraged Preference Optimization for Soft Preference Labels
Neural Information Processing Systems
However, human preferences can vary across individuals, and therefore should be represented distributionally.
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ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splatting
Neural Information Processing Systems
Omnidirectional (or 360-degree) images are increasingly being used for 3D applications since they allow the rendering of an entire scene with a single image.
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