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Tue Dec 04 12:30 PM -- 12:35 PM (PST) @ Room 220 E
Evolved Policy Gradients
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Tue Dec 04 12:35 PM -- 12:40 PM (PST) @ Room 220 E
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning
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Tue Dec 04 12:40 PM -- 12:45 PM (PST) @ Room 220 E
Bayesian Model-Agnostic Meta-Learning
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Tue Dec 04 12:45 PM -- 12:50 PM (PST) @ Room 220 E
Probabilistic Neural Programmed Networks for Scene Generation
Oral
Tue Dec 04 12:50 PM -- 01:05 PM (PST) @ Room 220 E
Neural Ordinary Differential Equations
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Tue Dec 04 01:05 PM -- 01:10 PM (PST) @ Room 220 E
Bias and Generalization in Deep Generative Models: An Empirical Study
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Tue Dec 04 01:10 PM -- 01:15 PM (PST) @ Room 220 E
Robustness of conditional GANs to noisy labels
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Tue Dec 04 01:15 PM -- 01:20 PM (PST) @ Room 220 E
BourGAN: Generative Networks with Metric Embeddings
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Tue Dec 04 01:20 PM -- 01:25 PM (PST) @ Room 220 E
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
Oral
Tue Dec 04 01:25 PM -- 01:40 PM (PST) @ Room 220 E
How Does Batch Normalization Help Optimization?
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Video]
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Tue Dec 04 01:40 PM -- 01:45 PM (PST) @ Room 220 E
Training Neural Networks Using Features Replay
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Tue Dec 04 01:45 PM -- 01:50 PM (PST) @ Room 220 E
Step Size Matters in Deep Learning
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Tue Dec 04 01:50 PM -- 01:55 PM (PST) @ Room 220 E
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
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Tue Dec 04 01:55 PM -- 02:00 PM (PST) @ Room 220 E
Hierarchical Graph Representation Learning with Differentiable Pooling