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Workshop
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How many trained neural networks are needed for influence estimation in modern deep learning?
Sasha (Alexandre) Doubov · Tianshi Cao · David Acuna · Sanja Fidler
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Workshop
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Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation
Melrose Roderick · Felix Berkenkamp · Fatemeh Sheikholeslami · J. Zico Kolter
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Workshop
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Periodic Signal Recovery with Regularized Sine Neural Networks
David A. R. Robin · Kevin Scaman · marc lelarge
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Poster
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Tue 14:00
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On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias
Itay Safran · Gal Vardi · Jason Lee
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Poster
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Tue 9:00
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Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs
Etienne Boursier · Loucas PILLAUD-VIVIEN · Nicolas Flammarion
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Poster
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Wed 14:00
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Invertible Monotone Operators for Normalizing Flows
Byeongkeun Ahn · Chiyoon Kim · Youngjoon Hong · Hyunwoo Kim
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Poster
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Thu 9:00
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Whitening Convergence Rate of Coupling-based Normalizing Flows
Felix Draxler · Christoph Schnörr · Ullrich Köthe
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Poster
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Tue 9:00
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NSNet: A General Neural Probabilistic Framework for Satisfiability Problems
Zhaoyu Li · Xujie Si
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Poster
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Thu 14:00
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Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models
Chen Henry Wu · Saman Motamed · Shaunak Srivastava · Fernando D De la Torre
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Poster
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Thu 14:00
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Modular Flows: Differential Molecular Generation
Yogesh Verma · Samuel Kaski · Markus Heinonen · Vikas Garg
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Workshop
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Modular Flows: Differential Molecular Generation
Yogesh Verma · Samuel Kaski · Markus Heinonen · Vikas Garg
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Workshop
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Fri 10:15
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Hydranet: A Neural Network for the estimation of Multi-valued Treatment Effects
Borja Velasco · Jesus Cerquides · Josep Arcos
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