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Poster
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Wed 9:00
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A Quantitative Geometric Approach to Neural-Network Smoothness
Zi Wang · Gautam Prakriya · Somesh Jha
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Workshop
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Fri 3:50
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Post-Training Neural Network Compression With Variational Bayesian Quantization
Zipei Tan · Robert Bamler
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Workshop
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Post-Training Neural Network Compression With Variational Bayesian Quantization
Zipei Tan · Robert Bamler
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Workshop
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Do Neural Networks Trained with Topological Features Learn Different Internal Representations?
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Poster
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Wed 14:00
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Data-Efficient Augmentation for Training Neural Networks
Tian Yu Liu · Baharan Mirzasoleiman
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Invited Talk
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Thu 12:30
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The Forward-Forward Algorithm for Training Deep Neural Networks
Geoffrey Hinton
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Poster
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Thu 9:00
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Bridging the Gap: Unifying the Training and Evaluation of Neural Network Binary Classifiers
Nathan Tsoi · Kate Candon · Deyuan Li · Yofti Milkessa · Marynel Vázquez
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Workshop
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Physically-primed deep-neural-networks for generalized undersampled MRI reconstruction
Nitzan Avidan · Moti Freiman
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Poster
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Thu 9:00
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A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks
Mingrui Liu · Zhenxun Zhuang · Yunwen Lei · Chunyang Liao
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Workshop
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Fri 6:30
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Has it Trained Yet? A Workshop for Algorithmic Efficiency in Practical Neural Network Training
Frank Schneider · Zachary Nado · Philipp Hennig · George Dahl · Naman Agarwal
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Workshop
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Renormalization in the neural network-quantum field theory correspondence
Harold Erbin · Vincent Lahoche · Dine Ousmane Samary
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Affinity Workshop
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Graph Convolutional Neural Network-based Quality Assessment of Light Field Images
Sana Alamgeer
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