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model simplification

11 papers

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Co-occurring keywords · papers mentioning both

inferential capability gap (1) relu nonlinearity (1) graph neural network (1) noise masking (1) scalable deep learning (1) neural texture (1) differentiable rasterization (1) l2 norm (1) rashomon set (1) hierarchical recurrent model (1)

Papers

DiffSoup: Direct Differentiable Rasterization of Triangle Soup for Extreme Radiance Field Simplification CVPR 2026 Explain It as Simple as Possible, but No Simpler – Explanation via Model Simplification for Addressing Inferential Gap (Abstract Reprint) IJCAI 2025 Simplification Is All You Need against Out-of-Distribution Overconfidence CVPR 2025 Towards Scalable and Deep Graph Neural Networks via Noise Masking AAAI 2025 Using Noise to Infer Aspects of Simplicity Without Learning NeurIPS 2024 Challenging the Semi-Supervised VAE Framework for Text Classification EMNLP 2021 In Search for a SAT-friendly Binarized Neural Network Architecture ICLR 2020 Simplifying Graph Convolutional Networks ICML 2019 The Lower The Simpler: Simplifying Hierarchical Recurrent Models NAACL 2019 Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach AISTATS 2018 Simplifying Mixture Models through Function Approximation NeurIPS 2006